elec 3104 digital signal processing - engineering 3104 digital signal processing summer session, ......
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School of Electrical Engineering & Telecommunications
Faculty of Engineering
ELEC 3104
Digital Signal Processing
Summer Session, 2014
ELEC3104: Digital Signal Processing
COURSE INTRODUCTION – Summer Session, 2014
Course Staff
Mentor/ Tutor: Dr. Karen Kua, Room G12A,
Course details
Credits
This is a 6 UoC course and the expected workload is 15–18 hours per week
throughout the 8 week semester.
Contact hours
The course consists of pre-recorded lecture videos provided for online download.
Contact hours are restricted to week 4 and 8 of summer session in addition to the
introductory lecture in week 1 and mid-session exam in week 5. There are 24 hours
of lab and 10 hours of tutorial in total.
The summer session officially runs over two periods, in addition to the introduction
in the first week, from 2/12/13 to 19/12/13, and from 6/01/14 to 19/02/14.
The introduction will be on the 3rd of December, 2013 from 2:00pm to 4:00 pm at
the Electrical Engineering Building in Room EE224.
For details of time and location for tutorials, laboratory and quiz refer the online
timetable: http://www.engineering.unsw.edu.au/electrical-engineering/elec3104-
summer-2014-timetable and Moodle.
Consultations: You are welcome to email the tutor or laboratory demonstrator, who
can answer your questions on this course and can also provide you with consultation
times. You are encouraged to ask questions during and after the lab and tutorial
classes.
Course Information
Context and aims
Signal Processing is the process of measuring, manipulating or analysing information.
Signals of interest include biomedical data, audio, still or moving images, radar, and
even DNA. Filtering techniques can be crucial in revealing and interpreting
information present in a signal. ELEC3104 Digital Signal Processing is an introductory
signal processing course which takes students through the steps necessary to design
and implement filters for a range of signals.
Aims
The course aims to equip students to do the following:
Deduce and understand the behaviour of a system, in terms of both its time
domain and frequency domain representations.
Identify the correct type of filter required for a given problem and be able to
demonstrate the design and implementation of a digital filter.
Explain the concept of aliasing and its effect on the design of practical
systems.
Understand multi-rate processing and multi-rate systems.
How does ELEC 3104 relate to other courses
This is a 3rd year course in the School of Electrical Engineering and
Telecommunications at the University of New South Wales. It is a core course for
students following a BE (Electrical) or (Telecommunications) program and other
combined degree programs, and an elective for Computer Engineering students.
Pre-requisites and Assumed Knowledge
The pre-requisite for this course is ELEC2134, Circuits and Signals. It is essential that
students are familiar with basic circuit theory, signal analysis and transform
methods. It is further assumed that students are familiar with the MATLAB
environment, and have good computer literacy.
Following courses
The course is a pre-requisite for all professional electives in the Signal Processing
group, including ELEC4621 Advanced Digital Signal Processing and ELEC4622
Multimedia Signal Processing
Learning outcomes
At the end of the course students should:
1. Be able to apply transform methods for the analysis of analogue and digital
linear time-invariant systems
2. Develop appropriate competency in converting between time and frequency
domain representations of signals and systems
3. Understand the practical aspects of sampling and reconstruction and be able
to select a suitable sampling rate for a given signal processing problem
4. Be able to analyse and design analogue and digital filters to match desired
specifications
5. Demonstrate an understanding of the use and applications of the Discrete
Fourier transform
6. Have gained practical experience with the implementation of digital filters
7. Be able to design and implement simple multi-rate systems
This course is designed to provide the above seven learning outcomes which arise
from targeted graduate capabilities listed in Appendix A. The targeted graduate
capabilities broadly support the UNSW and Faculty of Engineering graduate
attributes (listed in Appendix D). This course also addresses the Engineers Australia
(National Accreditation Body) Stage I competency standard as outlined in Appendix
B.
Syllabus
Processing and analysis of continuous (analogue) and discrete-time (digital)
signals.
Sampling continuous signals: the sampling theorem, reconstruction, aliasing
and the z-transform.
Analogue filters: Butterworth filters.
Filter impulse and frequency responses, stability and digital oscillators.
The Discrete Fourier Transform (DFT).
Fundamentals of the design and realisation of finite impulse response (FIR)
and infinite impulse response (IIR) digital filters.
Linear and non-linear phase filters.
Decimation, interpolation, multi-rate digital signal processing.
Teaching strategies
Delivery Mode
Lectures will not be face-to-face, but provided as pre-recorded electronic
whiteboard based videos available for online download. In addition, tutorials and
laboratories are carried out in “block-mode”, where students are required to
physically be present on campus only in weeks 4 and 8 of the summer session, in
addition to the introductory lecture in week 1 and mid-session exam in week 5.
In weeks 4 and 8, students will undertake all labs and tutorials in an intensive
fashion. You will need to watch these pre-recorded electronic whiteboard based
video lectures in your own time before the tutorial classes. Advantages of the video
lectures are:
• You will be able to watch them at your own pace
• You can revisit the lecture content as many times as you like
• Things that you might miss in a normal live lecture (e.g. difficult mathematical
concepts) are available on the video lectures and/or via the tutorial classes
The pre-recorded lectures on video provide you with an opportunity to cover
material not yet covered in class. You should look through the laboratory notes to
decide what material you need to look over.
Teaching Methods
Pre-recorded electronic whiteboard based lectures = 36 hrs (mandatory)
Tutorials = 10 hrs (mandatory)
Labs = 24 hrs (mandatory)
Tutorials include some pre-recorded videos.
The rationale behind the teaching methods for this course:
The course is structured such that the pre-recorded lectures provide details
of course material so that you can understand each concept presented and
re-visit any difficult sections in detail.
The tutorials help to develop the required level of analytical skills that will be
used in this course.
Your mid-semester exam and the final exam will test your problem solving
skills and give you the opportunity to effectively communicate and
demonstrate your understanding of the principles in the course.
The laboratory classes are to ground the analytical subject material in a real-
world problem, where the skills and knowledge you learn throughout the
course will be applied in real engineering design work.
The lab exam will test your experimental skills learned in laboratory classes.
Learning in this course
You are expected to view all lectures, attends all tutorials, labs, and mid-semester
exams in order to maximise learning. You must prepare well for your laboratory
classes and your lab work will be assessed. In addition to the lecture notes/video,
you should read relevant sections of the recommended text. Reading additional text
would further enhance your learning experience. Group learning is also encouraged.
Tutorial classes
You should do all your problem sheet questions in advance of attending the tutorial
classes. Group learning is encouraged. Answers for these questions will not be
posted on the web, but will be discussed during the tutorial class and the tutor will
cover the more complex questions in the tutorial class.
In addition, during the tutorial class, 1-2 new questions that are not in your notes
will be provided by the tutor, for you to try in class. These questions and solutions
will not be made available on the web, so it is worthwhile for you to attend your
tutorial classes to gain maximum benefit from this course.
Laboratory program
The laboratory program is the centre of this course. Through the laboratory
component, you will progressively encounter the elements of the syllabus. The aim
of the laboratory component is to ground the analytical subject material in a real-
world problem, where the skills and knowledge you learn throughout the course will
be applied in real engineering design work. Throughout the semester, you will focus
on:
Sampling and reconstruction
Impulse and frequency response of systems
Description of filter types using poles and zeroes
Digital filter design including the use of DSP chip
Frequency domain analysis
Multi-rate processing
Students will be divided into 2 groups, A and B in Week 3. Please check your group
allocation on the course webpage (http://subjects.ee.unsw.edu.au/elec3104)
BEFORE your lab.
Laboratory Exemption
There is no laboratory exemption for this course. Regardless of whether equivalent
labs have been completed in previous courses, all students enrolled in this course for
Summer Session, 2014 must take the labs.
If, for medical reasons, (note that a valid medical certificate must be provided) you
are unable to attend a lab, you will need to apply for a catch-up lab during another
lab time, as agreed by the laboratory co-ordinator.
Assessment
The assessment scheme in this course reflects the intention to assess your learning
progress through the semester. Ongoing assessment occurs through the lab
checkpoints (see lab manual), lab exams and the mid-semester exam.
Mid-Semester Exam = 15%
Ongoing Lab Assessment and Lab Exams = 25%
Final Exam (3 hours) = 60%
Mid-Semester Examinations (15% total)
There will be one mid-semester examination, testing your understanding of the
principles and your analytical skills through a number of set problems.
Mid-Semester Exam: 15th January, 2014
Location of the exam will be confirmed prior to the exam
Covers lecture material from Chapters 1 to 6
If for medical reasons (note that a valid medical certificate must be provided), you
are unable to attend the mid-semester exam, you will be given an oral examination
of approximately 1 hour.
Laboratory Assessment (25%)
Throughout the semester, your progress in the laboratory will be assessed by your
lab tutor at a series of checkpoints (see lab manual) in every lab session, and also
through separate lab exams. You must pass the ongoing laboratory assessment
(check points) and lab exams to pass the course.
Ongoing Lab Assessment (Checkpoints):
At the checkpoints, you will present your work to your tutor, solve analytical
problems, write MATLAB code, explain the relevant concepts, and answer
questions on your labs. Marks will be assigned according to the broad criteria
explained in the laboratory notes. Feedback will be provided along with the
marks.
Laboratory Exams:
Laboratory Exams are closed book practical exams that include MATLAB coding
and analytical calculations. These exam questions will be based on what you have
learned in your laboratory classes and lectures. Each exam will be marked out of
10 and the marks will be released on Moodle.
Final Exam (60%)
There will be one final examination, testing your understanding of the principles and
your analytical skills through a number of set problems. If for medical reasons, (note
that a valid medical certificate must be provided to the university) you are unable to
attend the final exam, you will be given another exam (either oral or written, at the
discretion of the course convenor). You must pass this final exam to pass the
course.
The final exam will be 3 hours long
The final exam will cover all 9 chapters covered in the semester
University approved calculators are allowed.
Resources for Students
Textbooks
Prescribed textbook
S. K. Mitra, Digital Signal Processing, McGraw-Hill, 2011. This book is available
at the UNSW bookshop.
Reference books
J. Proakis & D. Manolakis, Digital Signal Processing, Prentice-Hall, 2007.
A. V. Oppenheim, R. W. Schafer, & P. Buck, Discrete-Time Signal Processing,
Prentice-Hall, 2010.
On-line resources
Moodle: As a part of the teaching component, Moodle will also be used. Mid-
semester examination results and lab marks will also be available via Moodle.
Course web page: http://subjects.ee.unsw.edu.au/elec3104
Mailing list
Announcements concerning course information will be given in the lectures,
via the course website http://subjects.ee.unsw.edu.au/elec3104 and/or on
Moodle.
Other matters
Academic Honesty and Plagiarism
Plagiarism is the unacknowledged use of other peoples work, including the copying
of assignment works and laboratory results from other students. Plagiarism is
considered a serious offence by the University and severe penalties may apply:
http://www.lc.unsw.edu.au/plagiarism
Continual Course Improvement
Students are advised that the course is under constant revision in order to improve
the learning outcomes of its students. Please forward any feedback (positive or
negative) on the course to the course convener or via the Course and Teaching
Evaluation and Improvement Process. You can also provide feedback to ELSOC who
will raise your concerns at student focus group meetings.
Administrative Matters
On issues and procedures regarding such matters as special needs, equity and
diversity, occupational health and safety, enrolment, rights, and general
expectations of students, please refer to the School policies:
http://scoff.ee.unsw.edu.au
Important Points Please note the following:
During your labs, 1-2 lab demonstrators will be present and will be able to guide
you in your laboratory-based learning.
You can get the lecture notes (hard copy) which contains the course outline,
MATLAB exercises, tutorial problem sheets, a sample mid-semester exam, a
sample final exam paper, references and a laboratory manual along with lecture
notes from the School Office.
A soft copy of both the lecture notes and the tutorial questions workbook is
available on the course website: http://subjects.ee.unsw.edu.au/elec3104
The pre-recorded lecture videos can be downloaded from:
http://eemedia.ee.unsw.edu.au/ELEC3104/index.htm. For any problems with
download etc, please contact the course convenor, Dr. Karen Kua on
Guidelines on learning that inform teaching at UNSW are available at
www.guidelinesonlearning.unsw.edu.au
Course Schedule
Week Topic
1-4
Chapter 1: Signals and Systems
Chapter 2: Digital Signal Processing Fundamentals
Chapter 3: Discrete-Time Systems
Chapter 4: Introduction to z-Transform
Chapter 5: Introduction to Digital Filters
Chapter 6: Discrete-Time Fourier Transform
5 Mid-semester Exam (Chapters 1-6): 15th January 2014
5-8 Chapter 7: Analogue Filter Design
Chapter 8: Digital Filter Design
Chapter 9: Multirate Digital Signal Processing
Final Exam (all chapters) during the week 14th to 19th Feb, 2014
Laboratory Schedule
Week, Day Group Suggested Lab work Required
Reading
4, Tue A Lab 1 - Introduction to TIMS and MATLAB
Matlab Exercises,
Chapters 1 &2 4, Wed B
4, Tue A Lab 2 - Sampling and Reconstruction Chapters 1 &2
4, Wed B
4, Fri A and B Lab Exam 1 Chapters 1 &2
4, Fri A and B Lab 3 - Impulse Response, Frequency
Response, and Poles/Zeros of Systems Chapters 1 to 5
8, Wed A and B Lab Exam 2 Chapters 1 to 5
8, Wed A and B Lab 4 - Digital Filters Chapters 1 to 8
8, Fri A and B Lab 5 Interpolation and Decimation Chapters 1 to 9
8, Fri A and B Lab Exam 3 Chapters 1 to 9
Appendix A: Targeted Graduate Capabilities The Electrical Engineering and Telecommunications programmes are designed to address the
following targeted capabilities which were developed by the school in conjunction with the
requirements of professional and industry bodies:
The ability to apply knowledge of basic science and fundamental technologies;
The skills to communicate effectively, not only with engineers but also with the wider
community;
The capability to undertake challenging analysis and design problems and find optimal solutions;
Expertise in decomposing a problem into its constituent parts, and in defining the scope of each
part;
A working knowledge of how to locate required information and use information resources to
their maximum advantage;
Proficiency in developing and implementing project plans, investigating alternative solutions, and
critically evaluating differing strategies;
An understanding of the social, cultural and global responsibilities of the professional engineer;
The ability to work effectively as an individual or in a team;
An understanding of professional and ethical responsibilities;
The ability to engage in lifelong independent and reflective learning.
Appendix B: Engineers Australia (EA) Stage 1 Competency standard
Program Intended Learning Outcomes ELEC3104
PE1
: K
no
wle
dge
Bas
e
PE1.1 Knowledge of Science and Engineering Fundamentals
PE1.2 In-depth technical competence in at least one eng discipline
PE1.3 Techniques and resources
PE1.4 General Knowledge
PE2
: En
gin
eeri
ng
Ab
ility
PE2.1 Ability to undertake problem identification, formulation, and solution
PE2.2 Understanding of social, cultural, global and environmental responsibilities and the need
to employ principles of sustainable development
PE2.3 Ability to utilise a systems approach to complex problems and to design and operational
performance
PE2.4 Proficiency in engineering design
PE2.5 Ability to conduct an engineering project
PE2.6 Understanding of the business environment
P E 3: P r of e ss io n al
A tt ri b u te s PE3.1 Ability to communicate effectively, with the engineering team and with the community at
large
PE3.2 Ability to manage information and documentation
PE3.3 Capacity for creativity and innovation
PE3.4 Understanding of professional and ethical responsibilities, and commitment to them
PE3.5 Ability to function effectively as an individual and in multidisciplinary and multicultural
teams, as a team leader or manager as well as an effective team member
PE3.6 Capacity for lifelong learning and professional development
PE3.7 Professional Attitudes
Appendix C: Assessment methods linked to learning outcomes Learning outcomes
Assessment 1 2 3 4 5 6 7
Mid-semester examination (15 %) - - -
Lab assessment & exams (25%)
Final examination (60%) -
Learning outcomes:
1. Be able to apply transform methods to the analysis of analogue and digital linear time-
invariant systems
2. Develop the appropriate competency in converting between time and frequency domain
representations of signals and systems
3. Understand the practical aspects of sampling and reconstruction and be able to select a
suitable sampling rate for a given signal processing problem
4. Design and analyse analogue and digital filters for a given specification
5. Demonstrate an understanding of the use and applications of the Discrete Fourier transform
6. Have gained practical experience with the implementation of digital filters
7. Be able to implement a simple multi-rate system
Appendix D: Graduate Attributes The course delivery methods and course content address a number of core UNSW
graduate attributes, as follows:
Analytical skills, critical thinking and creative problem solving will be
developed by the laboratory experiments and interactive checkpoint
assessments and lab exams during the labs.
Self-assessment of independent and reflective learning is made available
through a series of tutorials spanning the duration of the course together
with the video-based learning material. The laboratory program fosters
independent learning.
Demonstration of the understanding of principles, and the effective use and
communication of relevant information will be tested in depth, via the mid-
semester examination and the final examination.