# L esson plan lp-ec-181403 lp rev. No: 00 Date: 12. 12. 2011 Page 1 of 6

Скачать 106.12 Kb.
 Название L esson plan lp-ec-181403 lp rev. No: 00 Date: 12. 12. 2011 Page 1 of 6 Дата 08.10.2012 Размер 106.12 Kb. Тип Документы

DOC/LP/01/28.02.02

LP-EC-181403

LP Rev. No: 00

Date: 12.12.2011

Page 1 of 6
###### Sub Code & Name : 181403PROBABILITY AND RANDOM PROCESSES

Unit: I Branch: EC Semester : IV

Unit syllabus:

UNIT I RANDOM VARIABLES

Discrete and continuous random variables – Moments - Moment generating functions and their properties. Binomial, Poisson ,Geometric, Uniform, Exponential, Gamma and normal distributions – Function of Random Variable.

Objective: To enable the students to have a fundamental knowledge of the basic probability concepts and to have a well-founded knowledge of standard distributions which can describe real life phenomena

 Session No Topics to be covered Time Ref Teaching Method 1 Introduction, Random variables, discrete and continuous random variables, cumulative distribution function 50 1 Black Board and Chalk 2 Probability mass/density function Moments, moment generating function, probability generating function. 50 3 Moments, moment generating function, probability generating function 50 4,5 Examples of discrete random variables- Binomial Poisson variates . Poisson Distribution 100 6,7 Poisson , Geometric distributions. 100 8,9 Continuous distributions - Uniform, Exponential distributions. 100 10 Gamma distribution, Normal distribution 50 11 Normal Distribution 50 12 Function of Random Variable – discrete, continuous 50 13 Function of Random Variable, Revision 50 14 CAT 1 40

LP-EC-181403

LP Rev. No: 00

Date: 12.12.2011

Page 2 of 6
###### Sub Code & Name : 181403 PROBABILITY AND RANDOM PROCESSES

Unit: II Branch: EC Semester : IV

Unit syllabus:

UNIT II TWO DIMENSIONAL RANDOM VARIBLES

Joint distributions - Marginal and conditional distributions – Covariance - Correlation and Regression - Transformation of random variables - Central limit theorem (for iid random variables)

Objective: To acquire skills in handling situations involving more than one random variable and functions of random variables

 Session No Topics to be covered Time Ref Teaching Method 15 Two- dimensional random variables, Joint distribution functions, joint density functions. 50 1 Black Board and Chalk 16 Marginal distribution/density functions, conditional density functions, independent random variables 50 17 Correlation, covariance, Spearman’s rank correlation. 100 18 Regression curves 50 19 Regression curves 50 20 Regression lines, Rank correlation 50 21 Regression lines, Rank correlation 50 22 Tranformation of random variables 50 23 Tranformation of random variables 50 24 Central limit theorem 50 25 CAT 2 40

LP-EC-181403

LP Rev. No: 00

Date: 12.12.2011

Page 3 of 6
###### Sub Code & Name : 181403 PROBABILITY AND RANDOM PROCESSES

Unit: III Branch: EC Semester : IV

Unit syllabus:

UNIT III CLASSIFICATION OF RANDOM PROCESSES

Definition and examples - first order, second order, strictly stationary, wide-sense stationary and ergodic processes - Markov process - Binomial, Poisson and Normal processes - Sine wave process – Random telegraph process.

Objective:

Understand and characterize phenomena which evolve with respect to time in probabilistic manner.

 Session No Topics to be covered Time Ref Teaching Method 26 Random processes- Introduction, classification. 50 2 Black Board and Chalk 27 Stationary processes- first order, second order, autocorrelation function, autocovariance function , WSS 50 28,29 WSS processes, Problems, Ergodic Processes 100 30 Markov process, Bernoulli process 50 31 Binomial process 50 32 Poisson process 50 33 Poisson process 50 34 Normal process 50 35 Normal process 50 36 Sine-wave process 50 37 Random Telegraph process 50 38 CAT 3 40

LP-EC-181403

LP Rev. No: 00

Date: 12.12.2011

Page 4 of 6
###### Sub Code & Name : 181403PROBABILITY AND RANDOM PROCESSES

Unit: IV Branch: EC Semester : IV

Unit syllabus:

UNIT IV CORRELATION AND SPECTRAL DENSITIES

Auto correlation - Cross correlation - Properties – Power spectral density – Cross spectral density - Properties – Wiener-Khintchine relation – Relationship between cross power spectrum and cross correlation function .

Objective:

To understand the relationship within and between random processes

 Session No Topics to be covered Time Ref Teaching Method 39 Properties of Auto-correlation, auto-covariance functions 50 2 Black Board and Chalk 40 Cross correlation function –properties. 50 46 Power spectral density, cross Power spectral density, properties 50 47 Problems 50 48 Wiener –Khintchine theorem 50 49 Problems 50 50 Relationship between cross power spectrum and cross correlation function 50 51 Problems 50 52 Revision 50 53 CAT 4 40

LP-EC-181403

LP Rev. No: 00

Date: 12.12.2011

Page 5 of 6
###### Sub Code & Name : 181403PROBABILITY AND RANDOM PROCESSES

Unit: V Branch: EC Semester : IV

Unit syllabus:

UNIT V LINEAR SYSTEMS WITH RANDOM INPUTS

Linear time invariant system - System transfer function – Linear systems with random inputs – Auto correlation and cross correlation functions of input and output – white noise.

Objective:

To be able to analyze the response of random inputs to linear time invariant systems.

 Session No Topics to be covered Time Ref Teaching Method 54 Linear systems with random inputs - LTI systems- System transfer function 50 2 Black Board and Chalk 55 Causal system, stable system, Autocorrelation and cross correlation functions of input and output 50 56 Autocorrelation and cross correlation functions of input and output 50 57 Problems 50 58 Problems 50 59 White Noise 50 60 Problems, Revision 50 61 Cat 5 40

LP-EC-181403

LP Rev. No: 00

Date:12.12.2011

Page 6 of 6
###### Sub Code & Name : 181403PROBABILITY AND RANDOM PROCESSES

Unit: Branch: EC Semester : IV

Course Delivery Plan:

 Week 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 I II I II I II I II I II I II I II I II I II I II I II I II I II I II I II Units CAT I CAT II CAT III CAT IV CAT V

TEXT BOOKS

1. Oliver C. Ibe, “Fundamentals of Applied probability and Random processes”, Elsevier, First Indian Reprint ( 2007) (For units 1 and 2)

2. Peebles Jr. P.Z., “Probability Random Variables and Random Signal Principles”, Tata McGraw-Hill Publishers, Fourth Edition, New Delhi, 2002. (For units 3, 4 and 5).

REFERENCES

1. Miller,S.L and Childers, S.L, “Probability and Random Processes with applications to Signal Processing and Communications”, Elsevier Inc., First Indian Reprint 2007.

2. H. Stark and J.W. Woods, “Probability and Random Processes with Applications to Signal Processing”, Pearson Education (Asia), 3rd Edition, 2002.

3. Hwei Hsu, “Schaum’s Outline of Theory and Problems of Probability, Random Variables and Random Processes”, Tata McGraw-Hill edition, New Delhi, 2004.

4. Leon-Garcia,A, “Probability and Random Processes for Electrical Engineering”, Pearson Education Asia, Second Edition, 2007.

5. Yates and D.J. Goodman, “Probability and Stochastic Processes”, John Wiley and Sons, Second edition, 2005.
 Prepared by Approved by Signature Name Dr. B. Thilaka Dr. R. Muthucumarasamy Designation Associate Professor HOD,AM Date 12.12.2011 12.12.2011

## Похожие:

Разместите кнопку на своём сайте:
Библиотека

База данных защищена авторским правом ©lib.znate.ru 2014
обратиться к администрации
Библиотека