Digital Signal Processing

Signal Processing

Created byDr Amol Prakash Bhagat

Last updated 7/2023

English

What you'll learn

Discrete –Time Signals and Systems: Introduction to DSP, Advantages, basic elements of DSP system, sampling theorem, A/D, D/A conversion, quantization
Elementary discretetime sequences. Discrete-time systems: description, representation, classification (linear, time invariant, static, casual, stable)
Analysis of DTLTI systems: The convolution sum, properties of convolution, Analysis of causal LTI systems, stability of LTI systems, step response of LTI system
Difference equation, recursive & non recursive systems, solution of difference equations, Impulse response of LTI recursive system. Correlation of discrete time
z- Transform and Analysis of LTI Systems: Definition of z- Transform, properties, rational z-Transforms, evaluation of the inverse z- Transforms
Analysis of LTI systems in z-domain, transient and steady-state responses, causality, stability, pole-zero cancellation, the Schur-Cohn stability test
Fourier Transforms, the DFT and FFT: Definition & properties of Fourier transform, relation with z-transform. Finite duration sequences and DFT
Properties, circular convolution, Fast algorithms for the computation of DFT: radix-2 and radix- 4 FFT algorithms
Design of Digital Filters: Classification of filters: LP, HP, BP, FIR and IIR filters, filter specifications. Design Windows and by Frequency sampling methods
Design of IIR filters from Analog filters using approximation of derivatives, Impulse invariant transformation, Bilinear transformation and Matched z-Transform
Realization of Discrete-Time systems: Structures for realization of Discrete-Time systems, realization of FIR systems: Direct Form, Cascade Form,
Frequency sampling and Lattice structures. Realization of IIR filters: Direct Form, Signal flow graph and Transposed structures, Cascade form,
Lattice and Lattice ladder. Realization for IIR systems

Course content

2 sections • 42 lectures • 20h 34m total length

Introduction to Digital Signal Processing, Digital Signal, Analog Signal24:34
Introduction to Digital Signal Processing, Digital Signal, Analog Signal
Signal Examples. Definition: Signal, Signal Source, System, Signal Processing17:30
Signal Examples. Definition: Signal, Signal Source, System, Signal Processing
Basic Elements of Digital Signal Processing System22:51
Basic Elements of Digital Signal Processing System, Advantages of Digital Signal Processing over Analog Signal Processing, Drawbacks of Digital Signal Processing, Difference between Analog Signal Processing System and Digital Signal Processing System
Analog to Digital Conversion, Digital to Analog Conversion, Sampling35:20
Analog to Digital Conversion, Digital to Analog Conversion, Sampling, Sampler, Sampled Signal, Quantization, Quantizer, Quantized Signal, Coding, Coder
Sampling of Analog Signal, Sampling Theorem, Sampling Frequency, Aliasing Effect57:24
Sampling of Analog Signal, Sampling Theorem, Sampling Frequency, Aliasing Effect, Nyquist Rate, Interpolation Function, Reconstruction of Analog Signal from Discrete Signal, Sampling Interval, Frequency of Analog Signal, Frequency of Sampled (Discrete-time Signal)
Example on Sampling Theorem, Identifying Sampling Frequency, Nyquist Rate30:28
Example on Sampling Theorem, Identifying Sampling Frequency, Identifying Nyquist Rate, Identifying Discrete Time Signal from Analog Signal
Quantization of Continuous Amplitude Signal, Coding, Quantization Error50:36
Quantization of Continuous Amplitude Signal, Coding, Quantization Error, Quantization Levels, Quantization Step Size or Resolution, Coding of Quantized Signal, Analog to Digital Signal Conversion
Discrete Time Signals, Representations of Discrete Time Signal19:51
Discrete Time Signals, Representations of Discrete Time Signal, Functional Representation, Graphical Representation, Sequence Representation, Tabular Representation
Elementary Discrete Time Signals30:37
Elementary Discrete Time Signals, Unit Sample or Unit Impulse Signal, Unit Step Signal, Unit Ramp Signal, Exponential Signal
Discrete Time Systems, Identifying Response of Discrete Time System1:08:51
Discrete Time Systems, Identifying Response of Discrete Time System, Identity System, Unit Delay, Unit Advance, Accumulator
Block Diagram Representation of Discrete-time Systems, Basic Building Blocks21:23
Block Diagram Representation of Discrete-time Systems, Basic Building Blocks of Discrete-time Systems, An Adder, A Constant Multiplier, A Signal Multiplier, Unit Delay Element, Unit Advance Element, Memory less elements, Elements with Memory
Block Diagram Representation of Discrete-time System, Realization14:03
Block Diagram Representation of Discrete-time System, Realization of Discrete-time System using Basic Building Blocks, Example on Block Diagram Representation of Discrete-time System
Classification of Discrete-Time Systems30:29
Classification of Discrete-Time Systems, Static Versus Dynamic Systems, Static Systems, Dynamic Systems, Examples
Time invariant versus time variant systems38:39
Time invariant versus time variant systems, time invariant systems, time variant systems, Classification of Discrete-time Systems, Example, Differentiator, Time Multiplier, Folder, Modulator
Linear Versus Non-linear Systems43:09
Linear Versus Non-linear Systems, Linear Systems, Non-linear systems, Identification of linear systems, Superposition Principle, Numerical
Causal Systems, Non-causal Systems27:09
Causal Systems, Non-causal Systems, Causal Versus Non-causal Systems, Identification of Causality of Discrete Time Systems
Stable Versus Unstable Systems18:03
Stable Systems, Unstable Systems, Stable Versus Unstable Systems, Identifying System Stable or Unstable
Classification of Signals30:28
Classification of Signals, Continuous and Discrete Signals, Energy and Power Signals, Periodic and Aperiodic Signals, Even and Odd Signals, Deterministic and Random Signals, Examples

Analysis of Discrete-Time Linear Time-Invariant Systems30:58
Analysis of Discrete-Time Linear Time-Invariant Systems, Methods for Analyzing DTLTI Systems
Response of Discrete-Time Linear Time-Invariant Systems24:20
Response of Discrete-Time Linear Time-Invariant Systems, Derivation of Convolution Formula, Convolution Summation, Steps in Computation of Convolution Sum
Convolution Sum, Identification of Convolution1:18:53
Convolution Sum, Identification of Convolution using Graphical Method, Identifying Response of Discrete-Time Linear Time-Invariant System using Convolution
Convolution Sum, Identification of Convolution33:52
Convolution Sum, Identification of Convolution using Tabular Method, , Identification of Convolution using Matrix Method, Identifying Response of Discrete-Time Linear Time-Invariant System using Convolution
Convolution Sum, Identification of Convolution19:01
Convolution Sum, Identification of Convolution using Mathematical Method, Identifying Response of Discrete-Time Linear Time-Invariant System using Convolution
Properties of Convolution30:56
Properties of Convolution, Commutative Property, Associative Property, Distributive Property, Identifying Impulse Response of LTI System
Causal Linear Time-Invariant Systems29:32
Causal Linear Time-Invariant Systems, Causality of LTI Systems, Causal Input Sequence, Response of Causal LTI System
Stability of Linear Time Invariant Systems16:50
Stability of Linear Time Invariant Systems, Condition for Stability of LTI Systems
Systems with Finite Duration and Infinite Duration Impulse Response14:18
Systems with Finite Duration and Infinite Duration Impulse Response, Finite Impulse Response (FIR) Systems, Infinite Impulse Response (IIR) Systems, FIR Systems, IIR Systems, Systems Characterized by Impulse Response
Discrete-Time Systems Described by Difference Equations10:34
Discrete-Time Systems Described by Difference Equations, Convolution and Difference Equation Comparison, IIR Systems Described by Difference Equations
Recursive and Non-recursive Discrete Time Systems34:57
Recursive and Non-recursive Discrete Time Systems, Difference between Recursive and Non-recursive Systems, Computing Response y(n) Efficiently by using Past Outputs
LTI Systems Characterized by Constant-Coefficient Difference Equations30:30
LTI Systems Characterized by Constant-Coefficient Difference Equations, Variant-Coefficient Difference Equations, Zero-State Response, Zero-Input Response, Total Response of LTI System, Forced Response, Natural Response, Free Response
Solution of Linear Constant-Coefficient Difference Equations25:53
Solution of Linear Constant-Coefficient Difference Equations, Homogeneous Solution, Particular Solution, Zero-Input Response
Identifying homogeneous solution from first order difference equation16:47
Identifying homogeneous solution from first order difference equation, identifying zero input response for the system described by first order difference equation, Example 1: Homogeneous Solution and Zero-Input Response
Identifying homogeneous solution from second order difference equation17:44
Identifying homogeneous solution from second order difference equation, identifying zero input response for the system described by second order difference equation, Example 2: Homogeneous Solution and Zero-Input Response
The Particular Solution of Difference Equation15:21
The Particular Solution of Difference Equation, Example 1: Determining Particular Solution of First Order Difference Equation
The Particular Solution of Difference Equation12:02
The Particular Solution of Difference Equation, Example 2: Determining Particular Solution of the Second Order Difference Equation
The Total Solution of The Difference Equation38:01
The Total Solution of The Difference Equation, Homogeneous Solution, Zero Input Response, Particular Solution, Total Solution, Zero State Response, Identification of Total Response of the LTI System using Difference Equation
Total Response of the Linear Time Invariant System53:02
Impulse Response of Linear Time-Invariant Recursive Systems15:51
Impulse Response of Linear Time-Invariant Recursive Systems, Finding Impulse Response of First-Order Recursive System
The Impulse Response of a Linear Time-Invariant Recursive System18:34
The Impulse Response of a Linear Time-Invariant Recursive System, Identifying The Impulse Response of a Second-Order Linear Time-Invariant Recursive System
Correlation of Discrete-Time Signals, Cross Correlation, Auto Correlation21:54
Correlation of Discrete-Time Signals, Cross Correlation, Auto Correlation, Convolution and Correlation Resembles
Correlation of Discrete-Time Signals, Cross Correlation Example43:43
Correlation of Discrete-Time Signals, Cross Correlation Example
Auto-correlation of Discrete-Time Signal, Correlation of Discrete-Time Signals19:02
Auto-correlation of Discrete-Time Signal, Correlation of Discrete-Time Signals

Requirements

No prerequisite needed. You will learn everything you need to know.

Description

Discrete –Time Signals and Systems: Introduction to DSP, Advantages, basic elements of DSP system, sampling theorem, A/D, D/A conversion, quantization. Elementary discretetime sequences. Discrete-time systems: description, representation, classification (linear, timeinvariant, static, casual, stable)
Analysis of DTLTI systems: The convolution sum, properties of convolution, Analysis of causal LTI systems, stability of LTI systems, step response of LTI systems, difference equation, recursive & non recursive discrete time systems, solution of difference equations, Impulse response of LTI recursive system. Correlation of discrete time signals
z- Transform and Analysis of LTI Systems: Definition of z- Transform, properties, rational z-Transforms, evaluation of the inverse z- Transforms, analysis of linear time invariant systems in z-domain, transient and steady-state responses, causality, stability, pole-zero cancellation, the Schur-Cohn stability test
Fourier Transforms, the DFT and FFT: Definition & properties of Fourier transform, relation with z-transform. Finite duration sequences and the discrete Fourier transform(DFT), properties, circular convolution, Fast algorithms for the computation of DFT: radix-2 and radix4 FFT algorithms
Design of Digital Filters: Classification of filters: LP, HP, BP, FIR and IIR filters, filter specifications. Design of FIR filters using Windows and by Frequency sampling methods. Design of IIR filters from Analog filters using approximation of derivatives, Impulse invariant transformation, Bilinear transformation and Matched z-Transformation, Commonly used Analog filters and IIR Filter design example
Realization of Discrete-Time systems: Structures for realization of Discrete-Time systems, realization of FIR systems: Direct Form, Cascade Form, Frequency sampling and Lattice structures. Realization of IIR filters: Direct Form, Signal flow graph and Transposed structures, Cascade form, Lattice and Lattice ladder. Realization for IIR systems

Who this course is for:

Undergraduate and Post Graduate Students

Digital Signal Processing

What you'll learn

Explore related topics

Course content

Discrete –Time Signals and Systems18 lectures • 9hr 41min

Analysis of Discrete-Time Linear Time-Invariant Systems24 lectures • 10hr 53min

Requirements

Description

Who this course is for: