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This document outlines the course file for ET-202 Signals and Systems taught during the 2016-2017 academic year by Dr. Monika Mittal at the National Institute of Technology Kurukshetra. The course covers topics such as types of signals, signal representations, classification of systems, linear time invariant systems, convolution, Fourier series, Fourier transforms, Laplace transforms, discretization of analog signals, characterization of discrete signals using Z-transforms, modeling, and random/stochastic signals. It includes 46 lectures covering these topics along with mid-semester and end-semester exams. Tutorial sessions are also included to support student learning.

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48 views9 pages

Couse File Sas

This document outlines the course file for ET-202 Signals and Systems taught during the 2016-2017 academic year by Dr. Monika Mittal at the National Institute of Technology Kurukshetra. The course covers topics such as types of signals, signal representations, classification of systems, linear time invariant systems, convolution, Fourier series, Fourier transforms, Laplace transforms, discretization of analog signals, characterization of discrete signals using Z-transforms, modeling, and random/stochastic signals. It includes 46 lectures covering these topics along with mid-semester and end-semester exams. Tutorial sessions are also included to support student learning.

Uploaded by

atulnishad
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as DOCX, PDF, TXT or read online on Scribd
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COURSE FILE

SIGNALS AND SYSTEMS


ET-202
2016-2017

Instructor

Dr. Monika Mittal


Department of Electrical Engineering
National Institute of Technology Kurukshetra
(HARYANA) 136119 India

Contact
Office: , Tel: 233388
mail:monika_mittalkkr@rediffmail.com
ET-202: SIGNALS AND SYSTEMS

Instructor: Dr. Monika Mittal

2016-2017

COURSE OUTLINE
SIGNALS
 Part 1: Types of signals
 Part 2: Signal representations
SYSTEMS
 Part 1: Classification
 Part 2: Linear time invariant system properties
CONVOLUTION THEOREM
 Part 1:Geometrical interpretation and applications
 Part 2: Concept of impulse response
ANALYSIS OF SIGNALS
 Part 1: Fourier series and its properties
 Part 2: Inversion of Fourier series

MID SEMESTER EXAMINATION


==============================================================

TRANSFORMS
 Part 1: Fourier transform
 Part 2: Inversion and applications of Fourier transform
 Part 3: Laplace transform
 Part 4: Inversion and applications of Laplace transform
MODELING
 Part 1: Modeling in terms of differential, equations, state variables, difference
equations and transfer functions.

MID SEMESTER EXAMINATION


==============================================================
DISCRETIZATION OF ANALOG SIGNALS
 Concept of sampling, theorem and its proof
 Effect of under sampling and recovery of analog signals from sampled signal
CHARACTERIZATION OF DISCRETE SIGNALS
 Part 1: In terms of impulse sequences
 Part 2: Z-transforms and its properties
 Part 3: Inversion and applications of Z-transforms
 Part 4: Modeling in terms of difference equations

MID SEMESTER EXAMINATION


=============================================================

RANDOM AND STOCHASTIC SIGNALS


 Part 1: Probability concepts
 Part 2: Random variable, its characterization and stochastic signal

END SEMESTER EXAMINATION


Tutorial #1

SIGNALS AND SYSTEMS


ET-202
2016-2017
Tutorial #2

SIGNALS AND SYSTEMS


ET-202
2016-2017
Tutorial #3

SIGNALS AND SYSTEMS


ET-202
2016-2017
Tutorial #4

SIGNALS AND SYSTEMS


ET-202
2016-2017
ET-202: Signals and Systems

Instructor: Dr. Monika Mittal

Course File
Lecture #1 : Introduction of the subject and syllabus.
Lecture #2,3 : Types of signals
Lecture #4 : Signal representations
Lecture #5-7 : Classification of systems
Lecture #8 : Numerical problems
Lecture #9,10 : Linear time invariant system properties
Lecture #11,12 : Convolution theorem geometrical interpretation and applications
Lecture #13,14 : Numerical problems
Lecture #15 : Concept of impulse response
Lecture #16 : Numerical problems
Lecture #17-19 : Introduction of Fourier series and its properties
Lecture #20 : Inversion of Fourier series
Lecture #21 : Numerical problems
Lecture #22-24 : Introduction of Fourier transform and its properties
Lecture #25 : Inversion and applications of Fourier transform
Lecture #26 : Numerical problems
Lecture #27-30 : Introduction of Laplace transform and its properties
Lecture #31,32 : Inversion and applications of Laplace transform
Lecture #33 : Numerical problems
Lecture #34 : Modeling in terms of differential equations
Lecture #35 : Modeling in terms of transfer functions
Lecture #36,37 : Modeling in terms of state variables equations
Lecture #38 : Concept of sampling, theorem and its proof
Lecture #39 : Effect of under sampling and recovery of analog signals from sampled
signal
Lecture #40,41 : Z-transform and its properties
Lecture #42 : Inversion and applications of Z-transform
Lecture #43 : Modeling in terms of difference equations
Lecture #44 : Numerical problems
Lecture #45 :Probability concepts
Lecture #46 :Random variable, its characterization and stochastic signals

(End of Course)

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