probability an rp course outline
TRANSCRIPT
National UniversityOF COMPUTER AND EMERGING SCIENCES
COURSE OUTLINE Probability and Random Processes
Code EE313 Title Probability and Random ProcessesCredit Hours 3 Semester
Course Objective
This course provides students with introduction to basic concepts of Probability, Random Variables and Random Processes and their applications in Signal Processing and Communication Systems. Understanding of the basic concepts and physical meaning of the mathematical results will be emphasized throughout.
Instructor Engr. Khalil Ullah Email [email protected]
Suggested Book (s) Probability and Random Processes for Electrical Engineering2nd Edition, By Alberto Leon-Garcia
Reference Book (s)
Probability and Random Processes for Electrical Engineers by John A. Gubnar
Probability and Random Processes, By Scott L. Miller and Donald G. Childers, 2004, Elsevier Academic Press
Probability and Random Processes, Schaum Outline
Web Resource (s)1. http://freevideolectures.com/Course/2324/Probability-and-Random-Processes 2. http://www.ece.uah.edu/courses/ee420-500/
Class Policy 1. Students must reach the class-room in time. Attendance shall be marked at the start of the class. Late-comers may join the class, but are not entitled to be marked as “present”.
2. Students failing to secure 80% attendance shall not be allowed to sit in the Final Examination.
3. Assignment submission dead-line must be observed. In case of late submission, 10% marks per day may be deducted after due date.
4. Mobile phones must be switched-off in the class-room.5. At final lecture at each 2nd week there will be a presentation by group of students related to applications of probability in E.E.
Evaluation Criteria Pre-Final Evaluation = 50 Marks Final Exam = 50 Marks
Mid-Term Exam 1 =15 Marks
Mid-Term Exam 2 =15 Marks
Assignments+ Presentations =10Marks
Quizzes = 10 Marks
Semester Weight = 100 Marks
Week
Topics to be Covered Quizzes and Assignment
s
1.
Introduction to probability and random processWhy probability for Electrical Engineers???The Modeling Process
a) Deterministic model b) Probabilistic modelExperiment, Random experiment, Event, Set operation, Sample space and its types.Different approaches to Probability
a) Classical approach to probability b) Empirical approach to probability c) Axiomatic approach to probability
2.
Computing probability using counting techniquesa) Rule of multiplication b) Rule of permutation c) Rule
of combinationLaws of probability
a) Complementation law b) Additional law of probability c) Conditional law of probability
Presentation1Assignment 1
3.
Laws of probabilityd) Multiplication law of probability e) Total law of
probability f) Bayes law of probabilityIndependent and Dependent events
4.
The concept of random variableTypes of random variables
a) Discrete random variable b) Continuous random variable
The probability functionThe probability density functionThe probability distributionConditional pdf and conditional cdfImportant Discrete random variablesBinomial random variable b) Geometric random variable
Quiz 1Assignment2Presentation2
5.
Important Continuous random variablesa) Exponential random variable b) Gamma random
variable MATLAB Exercise
6.
1st Mid Term ExaminationImportant Continuous random variables c) Uniform random variable d) Normal random variableMATLAB Exercise
Presentation 3
7.
The Expected value of a random variableThe Expected value of a function of a random variableMean and Variance of
a) Binomial random variable b) Poisson random variable c) Geometric random variable
d) Exponential random variable e) Uniform random variable f) Gamma random variable
g) Normal random variableApplication of the expected value of a random variable
Assignment 3
8.
Transform Methodsa) Moment generating function technique b)
Characteristic function technique c) Laplace transform d) Fourier transform
The Markov and Chebyshev inequalities
Presentation4
9
Reliability CalculationsThe concept of multiple random variableThe joint probability functionThe joint probability density functionThe joint cumulative probability distributionThe joint probability distributionMarginal probability density function of X and Y
Quiz 2
10
Expected value of a function of two random variablesThe covariance of two random variablesThe Correlation of two random variablesApplication of correlation and covariance of random variables
Presentation 4
11Definition of a random processSpecifying a random process2nd Mid Term Examination
12.
The Joint density function of time sampleThe joint distribution of time sampleMean Auto covariance and Autocorrelation of a random process
Quiz 3
13
Discrete time random processContinuous time random processStationary random process
Assignment 4Presentation 5
14Analysis and processing of a random signalPower spectral density functionResponse of linear system to random signal
15Markov ProcessesDiscrete time Markov chain
Presentation 6
16Continuous time Markov chain
Course Instructor Date: 28/08/2011Engr. Khalil Ullah