YoVDO

Signals and Systems

Offered By: NPTEL via YouTube

Tags

Electrical Engineering Courses Signal Processing Courses Control Systems Courses Differential Equations Courses Communication Systems Courses Fourier Analysis Courses Sampling Courses Convolution Courses Z-Transform Courses Laplace Transform Courses

Course Description

Overview

Instructor: Prof. K.S. Venkatesh, Department of Electrical Engineering, IIT Kanpur.

This course is a study of signals and systems, covering topics: formal definition of 'signal' and 'system', continuous and discrete signals, continuous and discrete-time systems, Linear Time-Invariant (LTI) systems, representation of continuous and discrete-time convolution, differential equations, difference equations, filters, periodic signals, Fourier series, Fourier transform and its properties, discrete-time Fourier transform, frequency response of continuous and discrete LTI systems, sampling, Laplace transform and its properties, inverse Laplace transform, z-transform and its properties, inverse z-transform.


Syllabus

Lecture-01 Signals.
Lecture-02 Domain & Range of signal.
Lecture-03 System Introduction.
Lecture-04 Signal Properties.
Lecture-05 Frequently used continuous signals.
Lecture-06 Frequently used discrete time signals.
Lecture-07 Transformations on time & Range.
Lecture-08 System Properties.
Lecture-09 System Properties.
Lecture-10 Communiction Diagram As a Test For Linearity & Time Invariance.
Lecture-11 LTI system.
Lecture-12 Representation of Discrete Time Convolution.
Lecture-13 Representation Of Continuous Time Convolution.
Lecture-14 Properties of Convolution.
Lecture-15 Differential Equations.
Lecture-16 Solving Differential Equation.
Lecture-17 Physical System Relation With Differential Equation.
Lecture-18 System Described by Differential Equation.
Lecture-19 System Described by Differential Equation.
Lecture-20 Difference Equation Intro.
Lecture-21 LTI Systems Described By Difference Equation.
Lecture-22 Filters.
Lecture-23 Implementation with Integrators.
Lecture-24 Theory of Signal Representation.
Lecture-25 Representation of Periodic Signal.
Lecture-26 Fourier Series.
Lecture-27 Fourier Spectrum.
Lecture-28 Fourier Transform.
Lecture-29 Properties of CTFT.
Lecture-30 Properties of CTFT.
Lecture-31 Frequency Response of Continuous System.
Lecture-32 Discrete Signals & System Representation.
Lecture-33 Discrete Time Fourier Transform.
Lecture-34 Properties of Discrete Time Fourier Transform.
Lecture-35 Frequency Response of Discrete LTI System.
Lecture-36 Ideal Sampling.
Lecture-37 Flat Top Sampling.
Lecture-38 Faithful Sampling.
Lecture-39 Interpolation.
Lecture-40 Laplace Transform.
Lecture-41 Inverse Laplace Transform.
Lecture-42 Properties of Laplace Transform.
Lecture-43 Z-Transform.
Lecture-44 Inverse Z Transform.
Lecture-45 Properties of Z Transform.


Taught by

nptelhrd

Tags

Related Courses

Fundamentals of CNNs and RNNs
Sungkyunkwan University via Coursera
Computer Vision with GluonCV (Indonesian)
Amazon Web Services via AWS Skill Builder
Computer Vision with GluonCV (Italian)
Amazon Web Services via AWS Skill Builder
Computer Vision with GluonCV (Korean)
Amazon Web Services via AWS Skill Builder
Computer Vision with GluonCV (Spanish)
Amazon Web Services via AWS Skill Builder