• 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

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