Digital Signal Processing (2023)

Signal Processing
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
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 signalsz- 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 testFourier 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 algorithmsDesign 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 exampleRealization 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
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