- Real Time Signals India
Basic and Advance DSP
About this course
Digital Signal Processing begins with a discussion of the analysis and representation of discrete-time signal systems, including discrete-time convolution, difference equations, the z-transform, and the discrete-time Fourier transform. Emphasis is placed on the similarities and distinctions between discrete-time. The course proceeds to cover digital network and nonrecursive (finite impulse response) digital filters. Digital Signal Processing concludes with digital filter design and a discussion of the fast Fourier transform algorithm for computation of the discrete Fourier transform.

Prerequisites
Students are expected to have the following background: Knowledge of basic computer science principles and skills, at a level sufficient to write a reasonably non-trivial computer program. Familiarity with linear algebra.
What you'll learn
Introduction to discrete linear systems
Discrete time signals
Special sequences
Shift invariance
Stability and causality
Impulse response
Difference equations
Discrete-Time Fourier Transform and Linear Time Invariant Systems
Transform definitions
Theorems
Frequency response of linear time invariant systems
Phase and group delays
Matlab computations
The Z transform
Z-transforms by summation of left, right, and two-sided sequences
Regions of convergence and Z-transform properties
Inverse Z-transform
Properties of digital filters
Averaging filter
Recursive smoother
First-order notch filter
Second-order unity gain resonator
All-pass filters
Comb filters
Equalization filters
Group delay, linear phase, all-pass, minimum phase
Fourier transforms, sampling
Fourier transform review
Sampling continuous-time signals: the sampling theorem
Aliasing
Re-sampling digital signalss
Fourier transforms, sampling
A/D conversion and quantization
D/A conversion
Polyphase decomposition
Polyphase DFT filterbanks
Bandpass sampling
The discrete Fourier transform
Definition of DFT and relation to Z-transform
Properties of the DFT
Linear and periodic convolution using the DFT
Zero padding, spectral leakage, resolution and windowing in the DFT
The fast Fourier transform
Decimation in time FFT
Decimation in frequency FFT
Digital filter design
Finite impulse response (FIR) filters
Window design techniques
Kaiser window design technique
Equiripple approximations
Infinite impulse response (IIR) filters
Bilinear transform method
Examples of bilinear transform method
Structures and properties of FIR and IIR filters and review
IIR - Direct, parallel and cascaded realizations
FIR - Direct and cascaded realizations
Coefficient quantization effects in digital filters