uČni naČrt predmeta / course syllabus · modulacija z amplitudnim, frekvenčnim in faznim...

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Elektronski sestavi Course title: Electronic Systems

Študijski program in stopnja Study programme and level

Študijska smerStudy field

Letnik Academic year

SemesterSemester

Telekomunikacije 2. stopnja 1. zimski Telecommunications 2nd level 1. Autumn

Vrsta predmeta / Course type Univerzitetna koda predmeta / University course code: Predavanja Lectures

Seminar Seminar

VajeTutorial

Klinične vajework

Druge oblike študija

Samost. delo Individ. work ECTS

30 30 120 6 Nosilec predmeta / Lecturer: Iztok Kramberger Jeziki / Languages:

Predavanja / Lectures: slovenski / SloveneVaje / Tutorial: slovenski / Slovene

Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:

Prerequisits:

Pogojev ni. None.

Vsebina:

Content (Syllabus outline):

Oscilatorji: osnovna zgradba in pogoja za oscilacije, tipi oscilatorjev, natančnost, stabilnost in točnost, fazni šum.

Podatkovni pretvorniki: osnove analogno digitalne in digitalno analogne pretvorbe, tipi pretvornikov, šum kvantizacije, nad‐vzorčenje, monolitnost, harmonska popačenja, diferenčna in integralna nelinearnost.

Signalni sintetizatorji: osnovna zgradba fazne zanke, numerično nadzorovani oscilatorji, fazno amplitudna pretvorba, neposredni digitalni sintetizator.

Digitalno filtriranje: osnove digitalnih filtrov, linearna diferenčna enačba, elementi digitalnih filtrov, kvantizacija, rekurzivna in ne‐rekurzivna oblika, z‐transformacija, ničle in poli, amplitudni in fazni odziv idealnih filtrov, linearni fazni odziv, digitalni resonator, inverzni filter.

Načrtovanje digitalnih filtrov z omejenim trajanjem impulznega odziva: uporaba diskretne

Oscillators: basic structure and oscillation conditions, types of oscillators, accuracy, stability and precision, phase noise.

Data converters: fundamentals of analog to digital and digital to analog conversion, converter types, quantization noise, oversampling, monolithism, harmonic distortion, differential and integral nonlinearity.

Signal synthesisers: basic structure of phase loop, numerically controlled oscillators, phase to amplitude conversion, direct digital synthesiser.

Digital filtering: fundamentals of digital filters, linear differential equation, elements of digital filters, quantization, recursive and non‐recursive form, z‐transformation, zeros and poles, amplitude and phase response of ideal filters, linear phase response, digital resonator, inverse filter.

Design of digital filters with finite impulse response: use of discrete Fourier

Fourierjeve transformacije, filtri z linearno fazo, metode načrtovanja, funkcije oken, stabilnost, red filtra, valovitost pasov, pasovna širina prehoda, alternativna okna, večpasovni filtri, osnovne strukture in izvedbe.

Načrtovanje digitalnih filtrov z neomejenim trajanjem impulznega odziva: pretvorba analognih filtrov v digitalno obliko, racionalna prenosna funkcija, stabilnost, bilinearna transformacija, osnovne strukture in izvedbe.

Digitalni pretvorniki: kaskada interpolatorja in decimatorja, digitalna pretvorba navzdol, digitalna pretvorba navzgor.

Tehnike digitalne modulacije: binarna modulacija z amplitudnim, frekvenčnim in faznim pomikom, kvadraturna modulacija s faznim pomikom, kvadraturna amplitudna modulacija, ortogonalno frekvenčno multipleksiranje (OFDM), neposredna digitalna sinteza (DDS).

transformation, filters with linear phase, design methods, window functions, stability, filter order, band ripple, transition bandwidth, alternative windows, multiband filters, basic structures and implementations.

Design of digital filters with infinitive impulse response: conversion of analog filters into digital form, rational transfer function, stability, bilinear transformation, basic structures and implementations.

Digital converters: cascade of interpolator and decimator, digital down conversion, digital up conversion.

Digital modulation techniques: binary amplitude‐shift keying, binary frequency‐shift keying, binary phase‐shift keying, quadrature phase‐shift keying, quadrature amplitude modulation, orthogonal frequency division multiplexing (OFDM), direct digital synthesis (DDS).

Temeljni literatura in viri / Readings: B. A. Shenoi: Introduction to Digital Signal Processing and Filter Design, Wiley‐Interscience, Hoboken,

2006. V. F. Kroupa: Direct Digital Frequency Synthesizers, Wiley‐IEEE Press, New York, 1998. V. F. Kroupa: Frequency Stability: Introduction and Applications, Wiley‐IEEE Press, Hoboken, 2012. S. Winder: Analog and Digital Filter Design, Second Edition, Newnes, Elsevier Science, Boston, 2002.

Cilji in kompetence:

Objectives and competences:

Cilj tega predmeta je, da bodo študentje sposobni uporabe standardnih elektronskih gradnikov za izvedbo in analizo elektronskih sestavov.

The objective of this course is for students to be able to use standard building blocks for implementation and analysis of electronic systems.

Predvideni študijski rezultati:

Intended learning outcomes:

Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben izbrati in uporabiti primerne gradnike za

izvedbo elektronskih sestavov, uporabiti standardne elektronske sestave za

oblikovanje, generiranje, pretvorbo in obdelavo signalov,

pojasniti in analizirati delovanje elektronskega sestava ter ovrednotiti rezultate.

Knowledge and understanding: On completion of this course the student will be able to select and use appropriate building blocks for

electronic systems implementation, use of standard electronic systems for shaping,

generation, conversion and processing of signals,

clarify and analyse the electronic system operation and evaluate the results.

Prenosljive/ključne spretnosti in drugi atributi:

Transferable/Key skills and other attributes:

Spretnosti komuniciranja: ustno zagovarjanje laboratorijskih vaj, pisno izražanje pri dokumentiranju laboratorijskih vaj.

Uporaba informacijske tehnologije: iskanje podatkov o elektronskih gradnikih in sestavih ter njihovi uporabi preko spletnih strani.

Spretnosti računanja: določitev lastnosti elektronskih sestavov.

Reševanje problemov: izbira standardnih elektronskih sestavov za reševanje različnih sistemskih zahtev.

Praktične veščine: opravljanje laboratorijskih vaj in pridobivanje merilnih podatkov.

Communication skills: oral lab work defense, manner of written expression at lab work documentation.

Use of information technology: www searching for technical data of electronic devices and systems and their applications.

Calculation skills: determination of the electronic system properties.

Problem solving: selection of standard electronic systems for solving of different system requirements.

Practical skills: lab work performing and measurement data acquisition.

Metode poučevanja in učenja:

Learning and teaching methods:

predavanja, seminarske vaje, laboratorijske vaje.

lectures, tutorial, lab work.

Načini ocenjevanja:

Delež (v %) /Weight (in %)

Assessment:

laboratorijske vaje, test 1, test 2.

5025 25

lab work, test 1, test 2.

Opomba: Testa se lahko nadomestita s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: KRAMBERGER, Iztok, GRAŠIČ, Matej, ROTOVNIK, Tomaž. Door phone embedded system for voice

based user identification and verification platform. IEEE trans. consum. electron.. [Print ed.], Aug. 2011, vol. 57, no. 3, str. 1212‐1217.

KAČIČ, Zdravko, KRAMBERGER, Iztok. Postopek in naprava za gestikularno‐vizualno komunikacijo = Procedure and device for gesticulative‐visual communication : patent s spremenjenimi zahtevki Urada Republike Slovenije za intelektualno lastnino SI 21480 B, datum objave sprem. zahtevkov: 31. 1. 2013, Int. Cl. G09G 5/00; št. romunskega urada RO1019772 z dne 18. 6. 2012 : št. prijave P‐200300086, datum prijave 7. 4. 2003, datum objave patenta SI 21480 A: 31 .10. 2004. Ljubljana: Urad Republike Slovenije za intelektualno lastnino, 2013.

KRAMBERGER, Iztok. ESA/ESTEC projekt (Contract No. 4000106501/12/NL/KML): SDGS : final report. [S. l.: s. n., 2013]. 1 zv. (loč. pag.).

KRAMBERGER, Iztok. Aplikativno preizkušanje in nadgradnja programske opreme za sledenje in lokacijsko štetje ljudi v video tokovih. Maribor: Fakulteta za elektrotehniko, računalništvo in informatiko, 2010. 8 str.

KRAMBERGER, Iztok. Preizkušanje programskega modula krmiljenje sond. Maribor: UM FERI, 2012. 27 f., ilustr.

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Mobilni in vseprisotni elektronski sistemiCourse title: Mobile and Ubiquitous Electronic Systems




SemesterSemester

Telekomunikacije 2. stopnja 1. poletni Telecommunications 2nd level 1. Spring


Seminar Seminar

VajeTutorial

Klinične vajework



30 30 120 6 Nosilec predmeta / Lecturer: Matej Rojc Jeziki / Languages:



Prerequisits:

Priporočeno je znanje načrtovanja elektronskih sistemov, uporabe mikroprocesorjev, osnovna znanja digitalnega procesiranja signalov, osnov vgrajenih sistemov in programiranja.

Recommended is knowledge of electronic systems design, microprocessors, digital signal processing, embedded systems and programming.

Vsebina:


Uvod: predstavitev vseprisotnih elektronskih sistemov.

Vmesniki: vhodno/izhodne naprave, naravni vmesniki (govor, pisala, geste); komunikacijske rešitve med ljudmi in elektronskimi sistemi, interakcijski problemi, uporaba razpoznavanja slike; metodologije in procesi načrtovanja vmesnikov, metode implementiranja in primerjave vmesnikov; razvoj vmesnikov in interakcijskih tehnik.

Razpoznavanje okolja: sledenje gibanju, uporaba RFID tehnologije in inteligentnih senzorjev.

Prodorni sistemi z zavedanjem konteksta:

Introduction: presentation of ubiquitous electronic systems.

Interfaces: input/output devices, natural interfaces (speech, pens, gestures); communication solutions between humans and electronic systems, interaction problems; use of image recognition; methodologies and design processes of interfaces, implementation methods and comparisons of interfaces; development of interfaces and interaction techniques.

Environment recognition: tracing movements, use of RFID technology and intelligent sensors.

Context‐aware pervasive systems: mobile

mobilni sistemi za zaznavanje fizičnega okolja, pristopi prilagajanja elektronskih sistemov.

Okoljska inteligenca (AmI): okolja z elektronskimi sistemi, ki zaznavajo in se odzivajo na prisotnost ljudi; integracija mrežnih naprav v okolju; prilagajanje na uporabniške zahteve; zagotavljanje adaptabilnosti elektronskih sistemov.

Mobilni nosljivi sistemi: metode zlivanja senzorskih signalov; razpoznavanje konteksta mobilnih komunikacijskih sistemov; procesiranje senzorskih signalov in zlivanje podatkov; koncepti in metode integracije mobilnih elektronskih sistemov v oblačil, tekstilni senzorji, tehnologije pakiranja, komunikacijske rešitve, napajanje v nosljivih sistemih.

Načrtovanje vseprisotnih elektronskih sistemov za različna inteligentna okolja: analiza zmogljivosti, načrtovanje strojne, komunikacijske in programske opreme, uporaba prekinitev in sistemska integracija, optimizacija in testiranje.

Načrtovanje brezžičnih senzorskih omrežij. Brezžične tehnologije: bluetooth, zigbee, z‐

wave, wi‐fi.

systems for sensing physical environment, techniques for adaptation of electronic systems.

Ambient intelligence (AmI): environments with electronic systems that sense and react to human presence; integration of network devices in the environment; adaptation to user demands; assurance of adaptability of electronic systems.

Mobile wearable systems: methods for fusion of sensor signals; context recognition of mobile communication systems; processing sensor signals and data fusion; concepts and methods for integration of mobile electronic systems into clothes, textile sensors, packaging technologies, communication solutions, power supply solutions in wearable systems.

Designing ubiquitous electronic systems for various intelligent environments: performance analysis, designing hardware, communication and software equipment, applying interrupts and system integration, optimisation and testing.

Designing wireless sensor networks. Wireless technologies: bluetooth, zigbee, z‐

wave, wi‐fi,

Temeljni literatura in viri / Readings: U. Hansmann:Pervasive Computing: The Mobile World, Springer‐Verlag, New York, 2003. M. McCullough: Digital Ground: Architecture, Pervasive Computing, and Environmental Knowing, MIT

Press, Cambridge, 2005. E. Aarts and J. Encarnacao: True Visions: The Emergence of Ambient Intelligence, Springer, Eindhoven,

2006. Y.‐L. Theng and H. Duh: Ubiquitous computing: Design, Implementation and Usability, Information Science Reference, IGI Global, London, 2008.



Cilj predmeta, da bodo študenti razumeli teoretične osnove načrtovanja vseprisotnih elektronskih sistemov ter znali uporabiti tehnike načrtovanja vseprisotnih elektronskih sistemov za različna inteligentna okolja.

The objective of this course is for students to be able to demonstrate understanding of theoretical basis of ubiquitous electronic system design and use of techniques for designing ubiquitous electronic systems for various intelligent environments.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben Razložiti teoretične osnove tehnik načrtovanja

vseprisotnih sistemov ,

Knowledge and understanding: On completion of this course the student will be able to explain the theoretical basis of ubiquitous

načrtovati programsko opremo, uporabiti postopke analize zmogljivosti,

optimizacije in testiranja vseprisotnih elektronskih sistemov.

electronic system design techniques, design application software, apply techniques for performance analysis,

optimisation analysis and testing of ubiquitous electronic systems.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: ustni zagovor

laboratorijskih vaj, ustno izražanje pri ustnem izpitu.

Uporaba informacijske tehnologije: iskanje informacij na svetovnem spletu, uporaba programskih orodij za analizo in načrtovanje vseprisotnih elektronskih sistemov.

Spretnosti računanja: reševanje računskih nalog pri analizi in načrtovanju vseprisotnih elektronskih sistemov.

Reševanje problemov: načrtovanje in izvedba vseprisotnih elektronskih sistemov.

Transferable/Key skills and other attributes: Communication skills: oral lab work defence,

manner of expression at oral exam. Use of information technology: searching

information on the internet, use of software tools for analysis and design of ubiquitous electronic systems.

Calculation skills: solving analysis and design problems for analysis and design of ubiquitous electronic systems.

Problem solving: design and implementation of ubiquitous electronic systems.



predavanja, seminarske vaje, laboratorijske vaje, projekt.

lectures, tutorial, lab work, project.



Assessment:

opravljen projekt, ustni izpit.

60 %40 %

completed project, oral exam.

Reference nosilca / Lecturer's references: ROJC, Matej (urednik), CAMBELL, Nick (urednik). Coverbal synchrony in human‐machine interaction.

Boca Raton; London; New York: CRC Press, cop. 2014. XIV, 420 str. MLAKAR, Izidor, KAČIČ, Zdravko, ROJC, Matej. Describing and animating complex communicative

verbal and nonverbal behavior using Eva‐framework. Applied artificial intelligence, 2014, vol. 28, iss. 5, str. 470‐503.

MLAKAR, Izidor, KAČIČ, Zdravko, ROJC, Matej. TTS‐driven synthetic behavior generation model for embodied conversational agents. V: ROJC, Matej (ur.), CAMBELL, Nick (ur.). Coverbal synchrony in human‐machine interaction. Boca Raton; London; New York: CRC Press, cop. 2014, str. 325‐359.

MLAKAR, Izidor, ROJC, Matej. A new distributed platform for client‐side fusion of web applications and natural modalities : MWP platform. Applied artificial intelligence, 2013, vol. 27, iss. 7, str. 551‐574.

MLAKAR, Izidor, KAČIČ, Zdravko, ROJC, Matej. TTS‐driven synthetic behaviour‐generation model for artificial bodies. International journal of advanced robotic systems, ISSN 1729‐8806, 2013, vol. 10, št. 10, str. 1‐20.

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Načrtovanje in razvoj telekomunikacijskih storitevCourse title: Design and Development of Telecommunication Services




SemesterSemester



Seminar Seminar

VajeTutorial

Klinične vajework



30 30 120 6 Nosilec predmeta / Lecturer: Andrej Žgank Jeziki / Languages:



Prerequisits:

Priporočeno je splošno znanje telekomunikacij in računalništva.

General knowledge of telecommunications and computer science is recommended.

Vsebina:


Uvod. Storitve v telekomunikacijskih omrežjih: tipi,

arhitektura, načini izvajanja, regulacija. Osnovne in dopolnilne telefonske storitve. Konvergenca telekomunikacijskih storitev,

sistemov in terminalskih naprav. Sodobne storitve v internetnih omrežjih,

povezljivost storitev, mobilni prenos podatkov, internet stvari (IoT).

Načrtovanje in arhitektura telekomunikacijskih storitev.

Vsebina v telekomunikacijskih storitvah: vrste, kodiranje, procesiranje, izločanje informacij.

Koncepti razvoja telekomunikacijskih storitev:

Introduction. Services in telecommunication networks: types,

architecture, methods of service execution, regulation.

Basic and supplementary telephone services. Convergence of telecommunication services,

systems and terminal equipment. Advanced services in Internet networks, service

connectivity, mobile data, internet of things (IoT).

Design and architecture of telecommunication services.

Content in telecommunication services: type, coding, processing, information extraction.

omrežje NGN, omrežje 5G, omrežje IoT, vmesniki za razvoj storitev, standardizacija.

Načini razvoja telekomunikacijskih storitev in razvijalsko okolje in orodja.

Uporabniški vmesnik telekomunikacijske storitve.

Zaračunavanje storitev: časa, podatkov, vsebin, storitev. Sistemi za zaračunavanje.

Prihajajoči trendi na področju naprednih telekomunikacijskih storitev.

Concepts of telecommunication services’ design: NGN network, 5G network, IoT network, interfaces for service development, standardization.

Development of telecommunication services, development environment and tools.

Telecommunication service user interface. Service charging: time, data, content, service.

Billing systems. State‐of‐the‐art and future trends in the area of

advanced telecommunication services. Temeljni literatura in viri / Readings: T. Plevyak, V. Sahin: Next generation telecommunications networks, services, and management, IEEE

Press, Piscataway, Wiley, Hoboken, 2010. T. Janevski, NGN Architectures, Protocols and Services, John Wiley & Sons, Chichester, 2014. P. Lea: Internet of Things for Architects: Architecting IoT solutions by implementing sensors,

communication infrastructure, edge computing, analytics, and security, Packt Publishing, Birmingham, 2018.

E. Bertin: Evolution of telecommunication services : the convergence of telecom and internet : technologies and ecosystems, Springer, London, Heidelberg, New York, 2013.

G. Varrall: Making telecoms work : from technical innovation to commercial success, John Wiley & Sons, Chichester, 2012.



Cilj tega predmeta je študente naučiti načrtovanja in razvoja telekomunikacijskih storitev. Študent bo poznal različne koncepte telekomunikacijskih storitev in sistemov.

The objective of this course is to teach students how to design and develop telecommunication services. The student will understand concepts of telecommunication services and systems.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben pojasniti vlogo in tipe storitev v

telekomunikacijskih omrežjih. uporabiti znanje o načrtovanju in razvoju na

primeru telekomunikacijske storitve. razložiti koncepte in sodobne arhitekturne

pristope telekomunikacijskih storitev. preučiti vlogo vsebine in načinov

zaračunavanja storitev.

Knowledge and understanding: On completion of this course the student will be able to explain the role and types of telecommunication

services. apply knowledge about design and development

on the case of telecommunication service. interpret concepts and advanced architecture

approaches for telecommunication services. analyze the content influence and principles of

service charging mechanisms.


laboratorijskih vaj, pisno izražanje pri testih

Transferable/Key skills and other attributes: Communication skills: oral lab work defense,

manner of expression at the tests or written

oziroma pisnem izpitu. Uporaba informacijske tehnologije: uporaba

programskih orodij in telekomunikacijske makete.

Reševanje problemov: analiza, načrtovanje in razvoj telekomunikacijskih storitev.

exam. Use of information technology: use of

development software and telecommunication test environment.

Problem solving: analyze, design and development of telecommunication services.







Assessment:


5025 25


Opomba: Testa se lahko nadomestita s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: LOVRENČIČ, Tomaž, ŠTULAR, Mitja, KAČIČ, Zdravko, ŽGANK, Andrej. QoS estimation and prediction of

input modality in degraded IP networks. Wireless personal communications, Jan. 2015, vol. 80, iss.2, str. 837‐867.

SEPESY MAUČEC, Mirjam, KAČIČ, Zdravko, ŽGANK, Andrej. Speech recognition for interaction with a robot in noisy environment. Przeglęad Elektrotechniczny, 2013, r. 89, nr. 5, str. 162‐166.

ŽGANK, Andrej, KAČIČ, Zdravko. Predicting the acoustic confusability between words for a speech recognition system using Levenshtein distance. Elektronika ir elektrotechnika. [Print ed.], 2012, vol. 18, no. 8, str. 81‐84.

ŽGANK, Andrej. Three‐stage framework for unsupervised acoustic modeling using untranscribed spoken content. ETRI Journal, Oct. 2010, vol. 32, no. 5, 10 str.

REITER, Ulrich, ŽGANK, Andrej, et al. Factors influencing quality of experience. V: MÖLLERS, Sebastian (ur.), RAAKE, Alexander (ur.). Quality of experience : advanced concepts, applications and methods (T‐Labs series in telecommunication services). Heidelberg [etc.]: Springer, cop. 2014, str. 55‐72.

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Omrežja TCP/IP Course title: TCP/IP Networks




SemesterSemester



Seminar Seminar

VajeTutorial

Klinične vajework



45 30 105 6 Nosilec predmeta / Lecturer: Zmago Brezočnik Jeziki / Languages:



Prerequisits:

Priporočeno je osnovno znanje o računalniških omrežjih in protokolih.

Recommended is basic knowledge of computer networks and protocols.

Vsebina:


Uvod: protokolni sklad TCP/IP (protokol za nadzor prenosa/internetni protokol).

Protokoli sloja podatkovne povezave: PPP – protokol od točke do točke, tehnologije lokalnih računalniških omrežij, VLAN – navidezno lokalno računalniško omrežje.

Protokol za razreševanje naslovov (ARP) in protokol za povratno razreševanje naslovov (RARP).

Internetni protokol verzije 4 (IP/IPv4): uvod, naslavljanje, ovijanje in oblikovanje datagramov, fragmentiranje in defragmentiranje datagramov, usmerjanje datagramov in oddajanje več prejemnikom.

Internetni protokol verzije 6 (IPv6): spremembe, prehod, naslavljanje, ovijanje, oblikovanje, fragmentiranje, defragmentiranje in usmerjanje datagramov.

Protokoli za povečanje ali razširitev

Introduction: TCP/IP (Transport Control Protocol/Internet Protocol) protocol suite.

Data link layer protocols: PPP – Point to Point Protocol, local area network technologies, VLAN – Virtual Local Area Network.

Address Resolution Protocol (ARP) and Reverse Address Resolution Protocol (RARP).

Internet Protocol Version 4 (IPv4): introduction, addressing, datagram encapsulation and formatting, datagram fragmentation and reassembly, datagram routing and multicasting.

Internet Protocol Version 6 (IPv6): changes, transition, addressing, datagram encapsulation, formatting, fragmentation, reassembly, and routing.

Protocols for enhancement or expansion of IP capabilities: IP NAT – IP Network Address Translation Protocol, IPsec – IP Security Protocols, Mobile IP – IP Mobility Support.

sposobnosti IP: IP NAT – protokol prevajanja internetnih naslovov, IPsec – varnostni protokoli IP, Mobile IP – podpora mobilnosti IP.

Podporni protokoli: ICMP – internetni protokol za krmilna sporočila, IGMP – internetni protokol za upravljanje skupin, IPv6 ND – protokol za odkrivanje sosedov.

Usmerjanje v TCP/IP: RIP – protokol usmerjevalnih informacij, OSPF – odprti protokol z najkrajšo potjo najprej, BGP – protokol mejnih usmerjevalnikov.

Protokoli TCP/IP transportnega sloja: TCP – protokol za nadzor prenosa, UDP – uporabniški datagramski protokol, primerjava med TCP in UDP, naslavljanje v TCP in UDP (vrata in vtičnice), upravljanje povezav TCP, formatiranje sporočila TCP, krmiljenje pretoka TCP.

Protokoli TCP/IP aplikacijskega sloja: DNS – sistem domenskih imen, DHCP – protokol za dinamično konfiguriranje računalnikov, SNMP – preprosti protokol za upravljanje omrežja, FTP – protokol za prenos datotek, SMTP – preprosti protokol za prenos pošte, WWW – svetovni splet, HTTP – protokol za izmenjavo nadbesedil, NNTP – protokol za prenos novic po omrežju TCP/IP, protokoli TCP/IP za dostop na daljavo in priročni ukazi za administriranje.

IP support protocols: ICMP – Internet Control Message Protocol, IGMP – Internet Group Management Protocol, IPv6 ND – Neighbour Discovery Protocol.

TCP/IP routing: RIP – Routing Information Protocol, OSPF – Open Shortest Path First, BGP – Border Gateway Protocol.

TCP/IP transport layer protocols: TCP – Transport Control Protocol, UDP – User Datagram Protocol, comparison of TCP and UDP, TCP in UDP addressing (ports and sockets), TCP connection management, TCP message formatting, TCP flow control.

TCP/IP application layer protocols: DNS – Domain Name System, DHCP – Dynamic Host Configuration Protocol, SNMP – Simple Network Management Protocol, FTP – File Transfer Protocol, SMTP – Simple Mail Transfer Protocol, WWW – World Wide Web, HTTP – Hypertext Transfer Protocol, NNTP – TCP/IP Network News Transfer Protocol, TCP/IP remote access protocols and administration utilities.

Temeljni literatura in viri / Readings: C. M. Kozierok: The TCP/IP Guide: A Comprehensive, Illustrated Internet Protocols Reference, No Starch

Press, San Francisco, 2005. D. Comer: Internetworking with TCP/IP, Volume I, Sixth Edition, Pearson Prentice Hall, Upper Saddle

River, 2013. B. H. Forouzan: TCP/IP Protocol Suite, Fourth Edition, McGraw‐Hill, New York, 2010. Cisco Systems: Internetworking Technology Handbook, Fourth Edition, Cisco Press, Indianapolis, 2004. Cilji in kompetence:


Cilj predmeta je, da bodo študentje do podrobnosti razumeli delovanje protokolnega sklada TCP/IP in znali analizirati protokole v njem.

The objective of this course is that students will understand the details of the TCP/IP protocol stack and be able to analyze its protocols.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben pojasniti princip izmenjave informacij v

računalniških omrežjih, ki temeljijo na protokolnem skladu TCP/IP,

analizirati in primerjati ključne nižjeslojne protokole TCP/IP kot tudi protokole TCP/IP v uporabniškem sloju,

Knowledge and understanding: On completion of this course the student will be able to explain the principle of information exchange in

computer networks based on TCP/IP protocol suite,

analyse and compare TCP/IP lower‐layer core protocols as well as TCP/IP application layer protocols,

izbrati in uporabljati primerna programska orodja za analizo komunikacijskih protokolov,

konfigurirati omrežne naprave v omrežjih TCP/IP.

select and use appropriate software tools for analysis of communication protocols,

configure network devices in TCP/IP networks.


laboratorijskih vaj, pisno izražanje pri kvizu in pisnem izpitu.

Uporaba informacijske tehnologije: uporaba programskih orodij za analizo komunikacijskih protokolov.

Spretnosti računanja: izračunavanje mask podomrežij v dvojiškem in desetiškem številskem sistemu.

Reševanje problemov: reševanje podanih primerov analiziranja komunikacijskih protokolov in konfiguriranja omrežnih naprav pri laboratorijskih vajah.


manner of expression at quizzes and written exam.

Use of information technology: use of software tools for analysis of communication protocols.

Calculation skills: calculating subnet masks in binary and decimal number system.

Problem solving: solving of the given examples of communication protocols analysis and network devices configuration at lab work.







Assessment:

kvizi, laboratorijske vaje, test 1, test 2.

1040 25 25

quizzes, lab work, test 1, test 2.

Opomba: Testa se lahko nadomestita s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references:

MEOLIC, Robert, BREZOČNIK, Zmago. Flexible job shop scheduling using zero‐suppressed binary decision diagrams. Advances in production engineering & management, ISSN 1854‐6250. [Tiskana izd.], Dec. 2018, vol. 13, no. 4, str. 373‐388.

VLAOVIČ, Boštjan, VREŽE, Aleksander, BREZOČNIK, Zmago. Applying automated model extraction for simulation and verification of real‐life SDL specification with spin. IEEE access, ISSN 2169‐3536, 21 March 2017, vol. 5, str. 5046‐5058.

BREZOČNIK, Zmago, VLAOVIČ, Boštjan, VREŽE, Aleksander. Model checking using Spin and SpinRCP = Preverjanje modelov z uporabo orodij Spin in SpinRCP. Informacije MIDEM, Dec. 2013, vol. 43, no. 4, str. 235‐250.

VREŽE, Aleksander, VLAOVIČ, Boštjan, BREZOČNIK, Zmago. Sdl2pml ‐ tool for automated generation of Promela model from SDL specification. Computer standards & interfaces, [Print ed.], June 2009, vol. 31, iss. 4, str. 779‐786.

BREZOČNIK, Zmago, VLAOVIČ, Boštjan, VREŽE, Aleksander. SpinRCP : the eclipse rich client

platform integrated development environment for the spin model checker. V: 2014 International SPIN symposium on model checking of software : SPIN, July 21‐23, 2014 San Jose, USA : proceedings. New York: ACM, 2014, str. 125‐128.

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Prenosni sistemi Course title: Transmission Systems




SemesterSemester



Seminar Seminar

VajeTutorial

Klinične vajework



30 30 120 6 Nosilec predmeta / Lecturer: Iztok Kramberger Jeziki / Languages:



Prerequisits:

Pogojev ni. None.

Vsebina:


Predstavitev digitalnih prenosnih sistemov: zgodovinsko ozadje, današnji digitalni prenos, standardi digitalnih prenosov, prednosti digitalnih prenosov, poenostavljen prenosni sistem.

Principi sistemskega načrtovanja: splošen načrt, prenosne storitve, hipotetična referenčna vezja, objektivna ocena učinkovitosti.

Komunikacijski kanali in mediji: voden in ne‐voden medij, izbira prenosnega medija, parametri prenosnega kanala.

Prenos v osnovnem pasu: tipi binarnega kodiranja, učinkovitost binarnih kodov, podatkovno premešanje, razširjeni spekter, odkrivanje in popravljanje napak.

Dvosmernost: frekvenčna in časovna dvosmernost, zaščitni interval.

Tehnike dostopa: frekvenčna, časovna, kodna

Introduction to digital transmission systems: historical background, present‐day digital transmission, digital transmission standards, advantages of digital transmission, a simplified digital transmission system.

Principles of system design: general plan, transmission services, hypothetical reference circuits, performance objectives.

Communication channels in media: guided and unguided media, selection of transmittion media, parameters of transmission channel.

Baseband transmission: introduction, types of binary coding, performance of binary codes, data scrambling, spread spectrum, error detection and correction.

Duplexing: frequency and time duplexing, guard intervals.

Access techniques: frequency, time, code and space division.

in prostorska porazdelitev. Prenosni sistemi: digitalni kabelski sistemi,

optični prenosni sistemi, digitalni radijski sistemi, karakteristike prenosnih medijev, učinki šuma in interference, ojačevalniki, obnovitveni ponavljalniki. Preizkušanje, spremljanje in nadzor: tehnike preizkušanja, tehnike spremljanja učinkovitosti, izolacija napak, sistemi za nadzor in upravljanje.

Programsko definirani radijski sistemi: rekonfigurabilnost v heterogenih omrežjih, rekonfigurabilni terminali in omrežja, upravljanje profilov in radijskih virov, programsko in strojno rekonfiguriranje.

Transmission systems: digital cable systems, fibre optic transmission systems, digital radio systems, transmission media characteristics, noise and interference effects, amplifiers, regenerative repeaters.Testing, monitoring, and control: testing techniques, performance monitoring techniques, fault isolation, monitoring and control systems.

Software defined radio systems: re‐configurability in heterogeneous networks, reconfigurable terminals and networks, profile and radio resource management, software and hardware reconfiguration.

Temeljni literatura in viri / Readings: D. R. Smith: Digital Transmission Systems, Third Edition, Kluwer Academic Publishers, Boston, 2004. B. A. Carlson, B. P. Crilly, J. Rutledge: Communication Systems: An Introduction to Signals and Noise in

Electrical Communication, Fourth Edition, McGraw‐Hill, Boston, 2002. M. Dillinger, K. Madani, N. Alonistioti: Software Defined Radio: Architectures, Systems and Functions,

John Wiley & Sons Ltd., West Sussex, 2003. Cilji in kompetence:


Cilj tega predmeta je, da bodo študentje razumeli osnovne in napredne principe prenosnih sistemov ter pristope njihovega načrtovanja in analize na sistemskem nivoju.

The objective of this course is for students to understand basic and advance principles of transmission systems, their design and analysis at the system level.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razložiti splošne modele prenosnih sistemov in

navesti standarde digitalnih prenosov, njihove prednosti in slabosti,

razložiti kodirne postopke v osnovnem pasu, razložiti in predstaviti tehnike digitalne

modulacije in jih razporediti po namembnosti ter učinkovitosti, vključujoč uporabo OFDM modulacije in neposredne sinteze frekvenčnega spektra,

predstaviti in razložiti različne tipe prenosnih sistemov in pripadajoče arhitekture, vključno z ovrednotenjem karakteristik prenosnih medijev ter zmogljivosti prenosnih kanalov,

načrtovati in analizirati prenosne sisteme omejene kompleksnosti na sistemskem nivoju,

razložiti principe ter koncepte programsko definiranih radijskih sistemov na sistemskem nivoju.

Knowledge and understanding: On completion of this course the student will be able to explain common models of transmission

systems and list digital transmission standards, including their advantages and weaknesses,

explain coding approaches in the base band, explain and represent digital modulation

techniques and classify them by their purposes and performance, including OFDM modulation and direct spectrum synthesis,

represent and explain different types of transmission systems and appurtenant architectures, including evaluation of transmission media characteristics and available performance of the transmission channels,

design and analyse transmission systems of limited complexity at the system level,

explain principles and concepts of software defined radio systems at the system level.


laboratorijskih vaj, pisno izražanje pri testih oziroma pisnem izpitu.

Uporaba informacijske tehnologije: uporaba programskih orodij za simulacijo in načrtovanje prenosnih sistemov.

Spretnosti računanja: izvajanje računskih operacij nad rezultati simulacij in merilnimi rezultati.

Reševanje problemov: načrtovanje in simulacija preprostih prenosnih sistemov.


manner of expression at the tests or written exam.

Use of information technology: use of transmission system design and simulation software tools.

Calculation skills: performing calculating operations with simulation and measurement results.

Problem solving: designing and simulating of simple transmission systems.



predavanja, seminarske vaje, laboratorijske vaje,




Assessment:


5025 25


Opomba: Testa se lahko nadomestita s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: KRAMBERGER, Iztok, GRAŠIČ, Matej, ROTOVNIK, Tomaž. Door phone embedded system for voice

based user identification and verification platform. IEEE trans. consum. electron.. [Print ed.], Aug. 2011, vol. 57, no. 3, str. 1212‐1217.

KAČIČ, Zdravko, KRAMBERGER, Iztok. Postopek in naprava za gestikularno‐vizualno komunikacijo = Procedure and device for gesticulative‐visual communication : patent s spremenjenimi zahtevki Urada Republike Slovenije za intelektualno lastnino SI 21480 B, datum objave sprem. zahtevkov: 31. 1. 2013, Int. Cl. G09G 5/00; št. romunskega urada RO1019772 z dne 18. 6. 2012 : št. prijave P‐200300086, datum prijave 7. 4. 2003, datum objave patenta SI 21480 A: 31 .10. 2004. Ljubljana: Urad Republike Slovenije za intelektualno lastnino, 2013.

KRAMBERGER, Iztok. ESA/ESTEC projekt (Contract No. 4000106501/12/NL/KML): SDGS : final report. [S. l.: s. n., 2013]. 1 zv. (loč. pag.).

KRAMBERGER, Iztok. Aplikativno preizkušanje in nadgradnja programske opreme za sledenje in lokacijsko štetje ljudi v video tokovih. Maribor: Fakulteta za elektrotehniko, računalništvo in informatiko, 2010. 8 str. KRAMBERGER, Iztok. Preizkušanje programskega modula krmiljenje sond. Maribor: UM FERI, 2012. 27 f., ilustr.

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Računalniška multimediaCourse title: Computer Multimedia




SemesterSemester



Seminar Seminar

VajeTutorial

Klinične vajework



30 30 120 6 Nosilec predmeta / Lecturer: Borut Žalik Jeziki / Languages:



Prerequisits:

Pogojev ni. None.

Vsebina:


Uvod: kaj je računalniška multimedija, lastnosti multimedije, nelinearnost, interaktivnost, razvoj multimedije, uporaba multimedije.

Osnovne tehnike stiskanja podatkov: kodiranje s tekočo dolžino, skalarna kvantizacija, statistične tehnike, statistične tehnike s prilagajanjem, stiskanje s slovarjem, Grayeva koda, Golombova koda, Golomb‐Riceova koda.

Tehnike stiskanja rastrskih slik: ujemanje blokov, kodiranje rezanja blokov, FELICS, dekompozicija blokov, napovedno kodiranje z binarnim drevesom..

Stiskanje slik z izgubami: transformacija parov pikslov, ortogonalne transformacije, kvantizacija, Walsh‐Hadamardova transformacija, diskretna kosinusna

Introduction: what is computer multimedia, multimedia characteristics, non‐linearity, interactivity, development of multimedia, multimedia usage.

Basic data compression techniques: run‐length encoding (RLE), scalar quantisation, statistical methods, adaptive statistical methods, dictionary‐based methods, Gray coding, Golomb coding, Golomb‐Rice coding.

Techniques of raster images compression: block matching, block truncation coding, FELICS, flexible automatic block decomposition, binary tree predictive coding.

Lossy image compression: pair‐of‐pixels transformation, orthogonal transformation, quantisation, Walsh‐Hadamard transformation,

transformacija, valčna transformacija. JPEG, JPEG‐LS, JBIG. JPEG2000, SPIHT Fraktalno stiskanje. Stiskanje geometrijskih podatkov: stiskanje

oblakov točk, stiskanje trikotniških mrež, stiskanje vokselskih podatkov.

discrete cosine transform, wavelet transformation.

JPEG, JPEG‐LS, JBIG. JPEG2000, SPIHT Fractal compression. Compression of geometric data: point cloud

compression, compression triangular network, voxel data compression.

Temeljni literatura in viri / Readings: D. Salomon, G. Motta, D. Bryant, Data Compression ‐ The Complete Reference, Fourth Edition, Springer,

London, 2007. D. S: Taubman, M. W. Marcellin, JPEG2000 Image Compression Fundamentals, Standards and Practice,

Springer Science+Business Media, New York, 2013 N. Chapman, J. Chapman, Digital multimedia, John Wiley & Sons, Chichester, 2009. Cilji in kompetence:


Cilj predmeta je, da bodo študente razumeli teoretične osnove multimedijskih algoritmov, jih znali analizirati ter izpeljati nove postopke za računalniške multimedijske algoritme.

The objective of this course is for students to be able to understand the theoretical bases of multimedia algorithms, to analyse them and to design new variants of multimedia algorithms.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben razložiti teoretične osnove multimedijskih

algoritmov, primerjati multimedijske standarde in

algoritme med seboj, izbrati najprimernejše multimedijske algoritme

za dani problem, načrtovati nove izpeljanke multimedijskih

algoritmov.

Knowledge and understanding: On completion of this course the student will be able to explain the theoretical basis of multimedia

algorithms, compare different multimedia standards and

algorithms, select the best multimedia algorithm fort he

requested problem, design the new variants of multimedia

algorithms.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: pisanje strokovnega

poročila o laboratorijskih vajah, pisno izražanje na izpitih.

Uporaba informacijske tehnologije: pisanje računalniških programov, iskanje implementiranih (odprtokodnih) rešitev in drugih informacij na spletu.

Reševanje problemov: samostojno delo na projektu, ki vključuje izbiro obstoječih

Transferable/Key skills and other attributes: Communication skills: written report about the

lab work, manner of expression at written exams.

Use of information technology: software development, searching for implemented (open source) solutions and other information on the internet.

Problem solving: individual project work, including selection of the most suitable

algoritmov stiskanja glede na zahteve aplikacije ter načrtovanje lastnih algoritmov.

compression algorithms for a desired task, and design of own algorithms.



predavanja, seminarske vaje, laboratorijske vaje, reševanje domačih nalog.

lectures, tutorial, lab work, homework assignments.



Assessment:

laboratorijske vaje, 1. vmesni pisni izpit, 2. vmesni pisni izpit,

5025 25

lab work, 1st midterm written exam, 2nd midterm written exam,

Opomba: Če študent ni uspešno opravil obeh vmesnih izpitov, ju nadomesti s pisnim izpitom v deležu 50 %.Note: If a student has not completed both midterm exams, he replaces them with a written exam in the weight of 50%. Reference nosilca / Lecturer's references: ŽALIK, Borut, MONGUS, Domen, LUKAČ, Niko, RIZMAN ŽALIK, Krista. Efficient chain code compression

with interpolative coding. Information sciences, 2018, vol. 439/440, str. 39‐49. KOHEK, Štefan, STRNAD, Damjan, ŽALIK, Borut, KOLMANIČ, Simon. Interactive synthesis and

visualization of self‐organizing trees for large‐scale forest succession simulation. Multimedia systems, 2018, str. 1‐15.

LIPUŠ, Bogdan, ŽALIK, Borut. Robust watermarking of airborne LiDAR data. Multimedia tools and applications, 2018, vol. 77, iss. 21, str. 29077‐29097.

JESENKO, David, BRUMEN, Matej, LUKAČ, Niko, ŽALIK, Borut, MONGUS, Domen. Visualization and analytics tool for multi‐dimensional data. V: ICBDE 2018 : 2018 International Conference on Big Data and Education (ICBDE 2018) / Honolulu, Hawaii, USA/ 9‐11 March, 2018. [New York: ACM. cop. 2018], str. 1‐5.

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Širokopasovna omrežja in protokoliCourse title: Broadband Networks and Protocols




SemesterSemester



Seminar Seminar

VajeTutorial

Klinične vajework



30 30 120 6 Nosilec predmeta / Lecturer: Tatjana Kapus Jeziki / Languages:



Prerequisits:

Pričakovano je osnovno znanje o komunikacijskih omrežjih in protokolih, osnovno znanje objektno usmerjenega programiranja.

Recommended is basic knowledge of communication networks and protocols, as well as basic knowledge of object‐oriented programming.

Vsebina:


Uvod: razvoj telekomunikacij, politični in regulatorni vidiki.

Komunikacijska omrežja: zgradba omrežij, načini preklapljanja, parametri kakovosti storitev.

Govor prek IP: ozadje, kodiranje govora, prenos govora z IP, H.323, SIP, krmiljenje medijskih prehodov in arhitektura s programskimi stikali, VoIP in SS7.

Kakovost storitev v omrežjih IP: metode za dosego dobre kakovosti storitev, integrirane storitve, diferencirane storitve, MPLS.

Optična omrežja: SONET/SDH, omrežja WDM, optična omrežja z valovnodolžinskim usmerjanjem, elastična optična omrežja,

Introduction: telecommunications development, political and regulatory factors.

Communication networks: network structure, switching techniques, quality of service parameters.

Voice over IP: background, speech coding, transporting voice over IP, H.323, SIP, media gateway control and the softswitch architecture, VoIP and SS7.

Quality of service in IP networks: techniques for achieving good quality of service, integrated services, differentiated services, MPLS.

Optical networks: SONET/SDH, WDM networks, wavelength routing optical networks, elastic optical networks, optical packet switching,

optično paketno preklapljanje, optično preklapljanje rafalov.

Večstoritvena omrežja: namen in zgradba omrežij, širokopasovne dostopovne tehnologije z bakrenimi vodniki in optičnimi vlakni, tehnologije jedrnih omrežij, programsko določena omrežja.

optical burst switching. Multiservice networks: purpose and structure of

the networks, broadband copper and optical fibre access technologies, core network technologies, software‐defined networks.

Temeljni literatura in viri / Readings:

H. G. Perros: Connection‐oriented Networks: SONET/SDH, ATM, MPLS and Optical Networks, Wiley, Chichester, 2005.

R. Swale, D. Collins: Carrier‐Grade Voice over IP, Third Edition, McGraw‐Hill ‐ Education, 2013. A. S. Tanenbaum, D. Wetherall: Computer Networks, Fifth Edition, Pearson, Boston, 2014. J. M. Simmons: Optical Network Design and Planning, Springer International Publishing

Switzerland, 2014. L. Goleniewski: Telecommunications Essentials: The Complete Global Source, Second Edition,

Addison‐Wesley Professional, Upper Saddle River, 2007. Cilji in kompetence:


Cilj predmeta je, da bi študentje razumeli delovanje ter prednosti in slabosti različnih tehnologij sodobnih fiksnih širokopasovnih telekomunikacijskih omrežij ter znali uporabiti izbrano simulacijsko orodje za izgradnjo modela in analizo učinkovitosti novega protokola.

The objective of this course is for students to understand the operation and advantages and disadvantages of different technologies of modern fixed broadband telecommunications networks, as well as to be able to use a selected simulation tool to model and analyse performance of a new protocol.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben strokovno pojasniti bistvene značilnosti

delovanja vodovno in paketno preklapljanih prostranih omrežij,

z uporabo uveljavljenih strokovnih pojmov pojasniti vrste, namen in delovanje pomembnih žičnih in optičnih širokopasovnih omrežnih tehnologij glede na relevantne protokolne sloje,

povzeti prednosti in slabosti posameznih tehnologij ter razlike in podobnosti med njimi glede na zanje pomembne kriterije, kot sta na primer učinkovitost in zanesljivost,

uporabiti izbrano simulacijsko orodje za modeliranje in analizo učinkovitosti novih protokolov.

Knowledge and understanding: On completion of this course the student will be able to technically explain the essential characteristics

of circuit‐ and packet‐switched wide‐area network operation,

explain, by using the established technical terminology, the types, the purpose, and the operation of important wired and optical broadband network technologies with respect to relevant protocol layers,

summarize advantages and disadvantages of the individual technologies, as well as the differences and similarities between them regarding the relevant criteria, such as, for example, performance and reliability, apply a selected simulation tool for modelling and performance analysis of new protocols.

Prenosljive/ključne spretnosti in drugi atributi: Spretnosti komuniciranja: pisna poročila in

zagovor pri laboratorijskih vajah, pisno izražanje pri domačih nalogah in testih oziroma izpitu.

Uporaba informacijske tehnologije: uporaba orodij za simulacijo omrežij, v katerih ni potrebno programiranje, predvsem pa izbranega orodja, kjer je potrebno programiranje.

Reševanje problemov: reševanje manj zahtevnih problemov analize učinkovitosti in snovanja v omrežjih.

Transferable/Key skills and other attributes: Communication skills: written reports and oral

defence of lab work, writing homework assignments and tests or exam.

Use of information technology: use of network simulation tools requiring no programming and, primarily, of a selected tool which requires programming.

Problem solving: solving moderate network performance analysis and design problems.



predavanja, seminarske vaje, laboratorijske vaje, domače naloge.

lectures, tutorial, lab work, homework assignments.



Assessment:

domače naloge, laboratorijske vaje, test 1, test 2.

1040 25 25

homework assignments, lab work, test 1, test 2.

Opomba: Testa se lahko nadomestita s pisnim izpitom. Note: The tests may be replaced with a written exam. Reference nosilca / Lecturer's references: KAPUS, Tatjana. Modelling medium access control in IEEE 802.15.4 nonbeacon‐enabled networks with

probabilistic timed automata. Journal of mobile information systems, 2013, vol. 9, no. 2, str. 157‐188. KAPUS, Tatjana. Uporaba formalne verifikacije za analizo učinkovitosti omrežij. V: Omrežja

prihodnosti: zbornik referatov 30. delavnice o telekomunikacijah (VITEL). Ljubljana: Elektrotehniška zveza Slovenije, 2014, str. 65‐68.

KAPUS, Tatjana. Specifying and verifying external behaviour of fair input/output automata by using the temporal logic of actions. Informatica, 2015, vol. 26, no. 4, str. 685‐704.

KAPUS, Tatjana. Analysing the effect of CCA duration in 802.15.4 networks with hidden nodes by using PRISM. V: Proceedings of papers, 23nd Telecommunications Forum (TELFOR 2015). IEEE, 2015, str. 87‐90.

KAPUS, Tatjana. Using PRISM model checker as a validation tool for an analytical model of IEEE 802.15.4 networks. Simulation modelling practice and theory, 2017, vol. 77, str. 367‐378.

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Statistično procesiranje signalovCourse title: Statistical Signal Processing




SemesterSemester



Seminar Seminar

VajeTutorial

Klinične vajework



45 30 105 6 Nosilec predmeta / Lecturer: Zdravko Kačič Jeziki / Languages:



Prerequisits:

Priporočeno je osnovno znanje matematike, programiranja in obdelave signalov.

Recommended is basic knowledge of mathematics, programming, and signal processing.

Vsebina:


Teorija verjetnosti: dogodek, verjetnost in pogojna verjetnost, neodvisni dogodki.

Naključna spremenljivka in naključni vektor: osnovni koncept, porazdelitvena funkcija naključne spremenljivke, funkcija gostote verjetnosti naključne spremenljivke, Gaussova naključna spremenljivka, pogojna porazdelitvena funkcija, funkcija gostote pogojne verjetnosti, matematične operacije nad naključnimi spremenljivkami, koncept naključnega vektorja, skupna porazdelitev in gostota, pogojna porazdelitvena funkcija naključnega vektorja, funkcija pogojne gostote verjetnosti naključnega vektorja, statistična neodvisnost, matematične operacije nad naključnimi vektorji.

Probability theory: event, probability and conditional probability, independent events.

Random variable and random vector: basic concept, distribution function of random variable, density function of random variable, Gaussian random variable, conditional distribution/conditional density function, operations on random variables, concept of random vector, joint distribution and density, conditional distribution/conditional density function of random vector, statistical independence, operations on random vectors.

Random process: basic concept, classification of random processes, first‐/second‐order stationary process, wide‐sense stationarity, ergodicity, correlation and covariance, Gauss

Naključni proces: osnovni koncept, klasifikacija naključnih procesov, stacionarni procesi prvega/drugega reda, stacionarnost v širšem smislu, ergodičnost, korelacija in kovarianca, Gaussov in Poissonov naključni proces.

Ocena spektra: gostota spektra moči, pasovna širina, definicija šuma, beli in barvni šum.

Linearni sistemi z naključnimi vhodnimi signali: linearni sistem, prenosna funkcija, odziv na naključni signal, spektralne karakteristike, pasovna širina šuma, modeliranje izvorov šuma.

Filtriranje naključnih procesov: elementi determinističnega filtriranja signalov, filtriranje naključnih procesov, primerjava naključnih in determinističnih primerov filtriranja.

Markovov proces: definicija in primeri Markovovih procesov, izračun verjetnosti prehoda in verjetnosti stanja v Markovovih verigah, karakterizacija Markovovih verig, časovno zvezni Markovovi procesi, prikriti modeli Markova.

and Poisson random processes. Spectrum estimation: power spectrum density,

bandwidth, noise definition, white and coloured noises.

Linear systems with random inputs: linear system, transfer function, random signal response, spectral characteristics, noise bandwidth, modelling of noise sources.

Filtering of random processes: elements of deterministic signal filtering, filtering of random processes, comparison of deterministic and random case.

Markov processes: definition and examples of Markov processes, calculation of transition and state probabilities in Markov chains, characterisation of Markov chains, continuous time Markov processes, hidden Markov models.

Temeljni literatura in viri / Readings: B. Porat, Digital Processing of Random Signals: Theory and Methods, Dover Publications, New York,

2008. R. M. Gray, L. D. Davisson: An Introduction to Statistical Signal Processing, Cambridge University Press,

Cambridge, 2004. U. Spagnolini: Statistical Signal Processing in Engineering, John Wiley & Sons, Chichester, 2018.. S. Miller, D. Childers: Probability and Random Processes: With Applications to Signal Processing and

Communications, Elsevier Academic Press, Burlington, 2004. Cilji in kompetence:


Cilj predmeta je, da bodo študenti razumeli teoretične osnove postopkov statističnega procesiranja signalov, znali klasificirati posamezne stohastične procese ter uporabiti postopke statističnega procesiranja signalov pri obravnavi različnih stohastičnih signalov.

The objective of this course is for students to be able to demonstrate understanding of theoretical basis of statistical signal processing algorithms, classify different stochastic processes, and apply statistical signal processing algorithms in processing different stochastic signals.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben pojasniti osnove naključnih procesov, prepoznati karakteristike različnih naključnih

procesov in izvesti spektralno analizo naključnega procesa,

razumeti proces filtriranja naključnega procesa z linearnim sistemom,

UKnowledge and understanding: On completion of this course the student will be able to explain the fundamentals of random signals, recognise characteristics of different random

processes and conduct spectral analysis of random process,

demonstrate knowledge and understanding of

konstruirati digitalni filter in izvesti filtriranje naključnih procesov,

pojasniti osnove Markovovih procesov.

filtering random process with linear system, design digital filter and conduct filtering of

random processes, explain the basics of Markov processes.


laboratorijskih vaj, pisno izražanje pri pisnem izpitu.

Uporaba informacijske tehnologije: uporaba programskih orodij za statistično procesiranje signalov.

Reševanje problemov: načrtovanje in izvedba sistemov procesiranja naključnih signalov.


manner of expression at written exam. Use of information technology: use of statistical

signal processing software tools. Problem solving: designing and implementing

digital systems for random signal processing.



predavanja, seminarske vaje, laboratorijske vaje, seminarsko delo.

lectures, tutorial, lab work, seminar work.



Assessment:

opravljeno seminarsko delo, laboratorijske vaje, pisni izpit.

15 35 50

completed seminar work, lab work, written exam.

Reference nosilca / Lecturer's references: SEPESY MAUČEC, Mirjam, KAČIČ, Zdravko, VERDONIK, Darinka. Statistical machine translation of

subtitles for highly inflected language pair. Pattern recognition letters, ISSN 0167‐8655. [Print ed.], 1 Sep. 2014, vol. 46, str. 96‐103.

KOČEVAR, Marko, KOTNIK, Bojan, CHOWDHURY, Amor, KAČIČ, Zdravko. Real‐time fingerprint image enhancement with a two‐stage algorithm and block‐local normalization. Journal of real‐time image processing, Published online 19 July 2014, vol. , no. , str. 1‐4, ilustr., doi: 10.1007/s11554‐014‐0440‐z.

DONAJ, Gregor, KAČIČ, Zdravko. Context-dependent factored language models. EURASIP journal on audio, speech and music processing, ISSN 1687-4722. [Online ed.], 2017, vol. 2017, no. 6, str. 1-16. https://dk.um.si/IzpisGradiva.php?id=66442, doi: 10.1186/s13636-017-0104-6. [COBISS.SI-ID 20330774]..

SEPESY MAUČEC, Mirjam, BREST, Janez, BOŠKOVIĆ, Borko, KAČIČ, Zdravko. Improved differential evolution for large-scale black-box optimization. IEEE access, ISSN 2169-3536, Dec. 2018, iss. 1, vol. 6, str. 29516-29531, doi: 10.1109/ACCESS.2018.2842114. [COBISS.SI-ID 21465622].

KOČEVAR, Marko, KLAMPFER, Saša, CHOWDHURY, Amor, KAČIČ, Zdravko. Analysis of the Influence of non‐directional algorithms on fingerprint image enhancement. Elektronika ir elektrotechnika, [Print ed.], 2014, vol. 20, no. 6, str. 104‐109.

UČNI NAČRT PREDMETA / COURSE SYLLABUS Predmet: Strojno učenje za napredne telekomunikacijske storitve Course title: Machine learning for advanced telecommunication services


Študijska smer Study field


Semester Semester



Seminar Seminar

Vaje Tutorial

Klinične vaje work



30 30 120 6 Nosilec predmeta / Lecturer: Mirjam Sepesy Maučec Jeziki / Languages:

Predavanja / Lectures: slovenski / Slovene Vaje / Tutorial: slovenski / Slovene


Prerequisits:

Priporočeno je osnovno znanje linearne algebre, statistike, teorije verjetnosti in programiranja.

Recommended is the basic knowledge of linear algebra, statistics, probability theory and computer programming.

Vsebina:


Uvod: definicija umetne inteligence, pregled problemov v telekomunikacijah, ki jih lahko rešuje umetna inteligenca.

Inteligenca z uporabo logike, verjetnostna inteligenca.

Definicija strojnega učenja in njegova uporaba v telekomunikacijah, matematični in hevristični vidiki strojnega učenja, odkrivanje zakonitosti v podatkih.

Predprocesiranje: izbira atributov, transformacija atributov, krčenje dimenzij problema.

Nadzorovano in nenadzorovano učenje. Globoko učenje: eno‐ in večslojne nevronske

mreže, konvolucijska nevronska mreža, nevronska mreža s povratno zanko.

Metrike za ocenjevanje uspešnosti. Strojno učenje v analitiki omrežnih podatkov.

Introduction: definition of artificial intelligence, overview of telecommunication problems, tackled by AI.

Logical intelligence, probabilistic intelligence. Definition of machine learning and its usage in

telecommunication, mathematical and heuristic aspects of machine learning, discovering knowledge in data.

Pre‐processing: attributes selection, attributes transformation, data dimensionality reduction.

Supervised and unsupervised learning. Deep learning: single‐layer and multi‐layer

neural network, convolutional neural networks, recurrent neural networks.

Evaluation metrics. Machine learning in network data analytic. Machine learning in IoT networks. Machine learning in telecommunication

Strojno učenje v IoT omrežjih. Strojno učenje v telekomunikacijskih storitvah. Strojno učenje za izboljšanje QoE.

services. Machine learning for improving QoE.

Temeljni literatura in viri / Readings: I. Kononenko: Strojno učenje, Založba FE in FRI, 2005. R. E. Neapolitan, X. Jiang: Artificial Intelligence: With an Introduction to Machine Learning, Second

Edition, CRC, 2018. I. Goodfellow, Y. Bengio, A. Courville: Deep Learning (Adaptive Computation and Machine Learning),

MIT, Cambridge, MA, 2016. M. Gilbert (Ed.): Artificial Intelligence for Autonomous Networks, CRC, Boca Raton, FL, 2019. Cilji in kompetence:


Cilj tega predmeta je, da bodo študentje razumeli najpomembnejše koncepte iz umetne inteligence in strojnega učenja, uporabljene v telekomunikacijah in jih znali uporabiti v konkretnih primerih.

The objective of this course is for students to be able to demonstrate the understanding of most important concepts of artificial intelligence and machine learning, that are used in telecommunications, and to use them in concrete circumstances.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben uporabiti znanje o gradnji telekomunikacijskih

sistemov, ki vključujejo uporabo metod umetne inteligence,

uporabiti načine integracije znanja v telekomunikacijske inteligentne sisteme,

izbrati najprimernejši način strojnega učenja za izbrani telekomunikacijski problem.

Knowledge and understanding: On completion of this course the student will be able to use the knowledge of building the

telecommunication systems based on the use of the methods of artificial intelligence,

apply the methods of the integration of knowledge into telecommunication intelligent systems,

select the best machine learning method for the particular telecommunication problem.


laboratorijskih vaj, ustno izražanje pri kolokviju oziroma ustnem izpitu.

Uporaba informacijske tehnologije: uporaba sodobne informacijske tehnologije.

Reševanje problemov: načrtovanje in izvedba preprostih aplikacijskih rešitev.


manner of expression at preliminary oral assessment or final oral exam.

Use of information technology: use of advanced information technology.

Problem solving: designing and implementing of simple applications.



predavanja, seminarske vaje, seminarsko delo, laboratorijske vaje.

lectures, tutorial, seminar work, lab work.


Delež (v %) / Weight (in %)

Assessment:

opravljeno seminarsko delo, laboratorijske vaje, kolokvij.

20 35 45

completed seminar work, lab work, preliminary oral assessment.

Opomba: Kolokvij se lahko nadomesti z ustnim izpitom. Note: The preliminary oral assessment may be replaced with a final oral exam. Reference nosilca / Lecturer's references:

SEPESY MAUČEC, Mirjam, BREST, Janez. Slavic languages in phrase-based statistical machine translation: a survey. Artificial intelligence review, ISSN 0269-2821. [Print ed.], Jan. 2019, vol. 51, iss. 1, str. 77-117, ilustr., doi: 10.1007/s10462-017-9558-2. [COBISS.SI-ID 20561174]

SEPESY MAUČEC, Mirjam, BREST, Janez, BOŠKOVIĆ, Borko, KAČIČ, Zdravko. Improved differential evolution for large-scale black-box optimization. IEEE access, ISSN 2169-3536, Dec. 2018, iss. 1, vol. 6, str. 29516-29531, doi: 10.1109/ACCESS.2018.2842114. [COBISS.SI-ID 21465622]

SEPESY MAUČEC, Mirjam, DONAJ, Gregor. Morphology in statistical machine translation from English to highly inflectional language. Informacinąes technologijos ir valdymas, ISSN 1392-124X, 2018, vol. 47, no. 1, str. 63-74, doi: 10.5755/j01.itc.47.1.17887. [COBISS.SI-ID 21214742]

SEPESY MAUČEC, Mirjam, BREST, Janez. A review of the recent use of Differential Evolution for Large-Scale Global Optimization: An analysis of selected algorithms on the CEC 2013 LSGO benchmark suite. Swarm and evolutionary computation, ISSN 2210-6502, Available online 14 August 2018, str. 1-14, doi: 10.1016/j.swevo.2018.08.005. [COBISS.SI-ID 21644822]

SEPESY MAUČEC, Mirjam, KAČIČ, Zdravko, VERDONIK, Darinka. Statistical machine translation of subtitles for highly inflected language pair. Pattern recognition letters : an official publication of the International Association for Pattern Recognition, ISSN 0167-8655. [Print ed.], 1 Sep. 2014, vol. 46, str. 96-103, doi: 10.1016/j.patrec.2014.05.012. [COBISS.SI-ID 17900054]

UČNI NAČRT PREDMETA / COURSE SYLLABUSPredmet: Teorija informacij in kodiranjeCourse title: Information Theory and Coding




SemesterSemester



Seminar Seminar

VajeTutorial

Klinične v

uČni naČrt predmeta / course syllabus · modulacija z amplitudnim, frekvenčnim in faznim...

Documents