+ View more
Course overview
Signal Processing is used primarily in areas of the audio signal, speech processing, RADAR, seismology, audio, SONAR, voice recognition, and some financial signals. For example, Digital Signal Processing is used for speech compression for mobile phones, as well as speech transmission for mobile phones.This module has been designed to discuss classification of Discrete time signals and systems. The representation of signal in time domain as well as frequency domain is also explained in this module.
What will i learn?
- Discrete time signals
- Linear time invariant system
- z transform
- Fourier transform
- Convolution
Curriculum for this course
10 Lessons
03:32:06 Hours
Section A
10 Lessons
03:32:06 Hours
-
Lecture 1 Introduction to subject and signals
00:19:19
-
Lecture 2 DISCRETE TIME SIGNALS AND ITS CLASSIFICATION
00:27:16
-
Lecture 3 Classification of signals
00:21:03
-
Lecture 4 Discrete time systems
00:25:52
-
Lecture 5 Solution of constant coefficient Difference equation
00:17:52
-
Lecture 6 Z-Transform
00:26:25
-
Lecture 7 Properties of Z-Transform
00:21:03
-
Lecture 8 Inverse Z-Transform
00:16:31
-
Lecture 9 DISCRETE FOURIER TRANSFORM DFT
00:17:40
-
Lecture 10 PROPERTIES OF DFT
00:19:05
Frequently asked question
Introduction to subject and signals
Introduction to subject and various types of signals. Also discussed signal processing and advantages of Digital signal processing over analog signal processing.
DISCRETE TIME SIGNALS AND ITS CLASSIFICATION
Discussed various types of discrete time signals and sequences like imoulse sequence, unit step sequence etc. Also discussed various operations performed on signals.
Classification of signals
This lecture discussed different types of signals and their properties like periodicity, even and odd component. Basic operations like shifting , folding, time reversal etc is also discussed.
+ View more
Other related courses
About instructor
Student feedback
Write a public review