Applying Signal Processing with MATLAB

This two-day course shows how to analyze signals and design signal processing systems using MATLAB®, Signal Processing Toolbox, and DSP System Toolbox.

Topics include:

  • Creating and analyzing signals
  • Performing spectral analysis
  • Designing and analyzing filters
  • Designing multirate filters
  • Designing adaptive filters

Prerequisites
Attended "Comprehensive MATLAB" or equivalent experience using MATLAB and a good understanding of signal processing theory, including linear systems, spectral analysis, and filter design.

Course Outline

Day 1 of 2
Signals in MATLAB

Objective: Generate sampled and synthesized signals from the command line and visualize them. Create noise signals for a given specification. Perform signal processing operations like resampling, modulation, and correlation.

  • Creating discrete signals
  • Sampling and resampling
  • Visualizing signals
  • Modeling noise
  • Performing resampling, modulation, and correlation
  • Generating streaming signals
Spectral Analysis

Objective: Understand different spectral analysis techniques and the use of windowing and zero padding. Become familiar with the spectral analysis tools in MATLAB and explore nonparametric (direct) and parametric (model-based) techniques of spectral analysis.

  • Discrete Fourier transform
  • Windowing and zero padding
  • Power spectral density estimation
  • Time-varying spectra
  • Using a spectrum analyzer in MATLAB
Linear Time Invariant Systems

Objective: Represent linear time-invariant (LTI) systems in MATLAB and compute and visualize different characterizations of LTI systems.

  • LTI system representations
  • z-transform
  • Frequency and impulse response
  • Visualizing filter properties
  • Applying filters to finite and streaming signals
Day 2 of 2
Filter Design

Objective: Design filters interactively using the Filter Design and Analysis app. Design filters from the command line using filter specification objects.

  • Filter specifications
  • Interactive filter design
  • Common filter design functions
  • Filter design with filter specification objects
  • Reducing filter delay
  • Frequency-domain filtering
The Signal Analysis App

Objective: Learn to use a powerful all-in-one app for importing and visualizing multiple signals, performing spectral analysis on them, and designing and applying filters to the signals. Make simple statistical and cursor measurements on signals.

  • Browse signals and make simple measurements
  • Perform interactive spectral analysis
  • Design and apply filters to signals interactively
Multirate Filters

Objective: Understand principles of polyphase multirate filter design. Design multirate interpolating and decimating filters. Design multistage and narrow-band filters.

  • Downsampling and upsampling
  • Noble identities and polyphase FIR structures
  • Polyphase decimators and interpolators
  • Design multistage and interpolated FIR filters
Adaptive Filter Design

Objective: Design adaptive filters for system identification and noise cancellation.

  • Basics of adaptive filtering
  • Perform system identification
  • Perform noise cancellation
  • Improve adaptive filter efficiency

 

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