Training - Courses

MLSG: Signal Processing with MATLAB

This two-day course shows how to analyze signals and design signal processing systems using MATLAB^® and Signal Processing Toolbox^™. Parts of the course also use DSP System Toolbox^™.

Topics include:

Creating and analyzing signals
Using different spectral analysis tools
Designing and analyzing filters
Introduction to advanced filter design
Filter implementation issues
Processing streaming data with System objects

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	Detailed course outline

Day 1 of 2

Signals in MATLAB

Objective: Create and manipulate signals from the command line and using SPTool, a graphical interface in Signal Processing Toolbox. Visualize a signal in the time domain and create a noise signal for a given specification.

Creating and importing signals
Sampling and resampling
Visualizing signals
Modeling noise
Signal statistics and correlation

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
Spectrum objects
Time-varying spectra

LTI 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
Introduction to filtering
dfilt objects

Day 2 of 2
IIR Filter Design	Objective: Apply LTI system analysis to filter design and discuss the use of infinite impulse response (IIR) filters from initial performance specifications to digital design. Use the Filter Design and Analysis Tool (FDATool) graphical interface and design filters using filter specification objects. Filter specifications Filter design with graphical interfaces Filter design with filter specification objects
FIR Filter Design	Objective: Apply LTI system analysis to filter design and discuss the use of finite impulse response (FIR) filters from specification to digital design. Explore a variety of specialized filters. FIR design methods Standard band filters Arbitrary response filters Multiband filters Raised cosine filters Reducing filter delay Frequency-domain filtering
Advanced Filter Design	Objective: Discuss additional techniques for designing IIR and FIR filters; as well as adaptive and multirate filters. Explore a variety of practical applications. Median filtering Filter design with Filterbuilder Advanced IIR designs Advanced FIR designs Adaptive filters Multirate filters
Filter Implementation	Objective: Discuss the process of moving from filter design to hardware implementation and consider various architectures for filter realization and the effects of various quantization schemes. Filter architectures Filter realization Filter quantization
Stream Processing with System Objects	Objective: Process streaming data in MATLAB. Design algorithms in MATLAB using System objects. What is a System object Advantages of using a System object Stream processing with System object

Prerequisites

MATLAB^® Fundamentals or equivalent experience using MATLAB, and a good understanding of signal processing theory, including linear systems, spectral analysis, and filter design

Course Length - 2 days