|
Course
Highlights
This 2-day course presents signal processing in the MATLAB
environment, including the capabilities of the Signal Processing
and Filter Design toolboxes, as well as the basics of using
the Signal Processing Blockset in SIMULINK to analyze and
design a signal processing system. The first part includes
an introduction to signal processing with a concentration
on representations of signals in MATLAB, special analysis,
and working with linear, time- independent system models.
Also, it covers filter design, with comprehensive instruction
on FIR, IIR, adaptive, and multirate filters. Filter quantization
and implementation are also discussed. The second part will
emphasizes discrete-time simulations and includes topics on
buffering and vector operations, digital filter design and
implementation, transforms, power spectrum estimation
and Frame-based processing is
also discussed.
Prerequisites
Attended "MATLAB for Technical Computing" and "SIMULINK
for Dynamic System Modeling", or equivalent experience
using MATLAB & SIMULINK. Participants are expected to
have some exposure to signal processing techniques prior to
taking this course.
Course Outline
Part One
Introduction
- Course expectations
- Overview of MATLAB & SIMULINK and signal processing
products
- Signal processing uses
- Implementing signal processing systems
Signals
in MATLAB
Objective: learn how to create and manipulate signals using
the command line and the SPTool, a graphical user interface
(GUI) in the Signal Processing Toolbox. Throughout the course,
we will use the SPTool to analyze digital signals, filters,
and spectra.
- Creating and importing signals
- Sampling and resampling
- Visualizing signals
- Modeling noise
- Modulating
Spectral Analysis
Objective: gain an understanding of statistical signal
processing. Explore visualization and analysis of signals
in the time and frequency domains using spectral analysis.
- Signal statistics
- Discrete Fourier transform
- Power spectral density estimation
- Time-varying spectra
- Wavelets
LTI Systems
Objective: gain an understanding of linear time-independent
systems, the basis for filtering applications and the subject
of the majority of functions in the Signal Processing Toolbox.
We discuss various ways to represent such systems, both mathematically
and in MATLAB. Investigation of the basic input/output behavior
of these systems introduces filtering.
- LTI system representations
- The z-Transform
- Frequency and impulse response
- Introduction to filtering
- Cepstral analysis
IIR Filter Design
Objective: apply LTI system analysis to filter design and
discuss the use of IIR filters from initial performance specifications
to analog prototyping and digital design. The Filter Design
and Analysis Tool (FDATool) GUI is introduced, and will be
used for the remainder of the course to assist in filter design.
- Filter specifications
- Analog prototyping
- Filter design functions
- Introduction to the Filter Design and Analysis Tool
(FDATool)
FIR Filter Design
Objective: continue the application of LTI system analysis
to filter design, and discuss the use of FIR filters from
specification to digital design. Explore a variety of specialized
filters.
- FIR design methods
- Windowing
- Standard band filters
- Arbitrary response filters
- Multiband filters
- Raised cosine filters
- Frequency domain filtering
Part Two
Simulink Interface
Objective: This section introduces the Simulink interface and teaches basic concepts that will help new users to get comfortable with the environment.
- Simulink Library Browser
- Setting up a model
- Add and Connect blocks
- Input from MATLAB workspace
- Model callbacks
- Processing vectors and matrices
- Exploring the time scope
- Exploring the spectrum scope
- Initializing parameters and defining data
Signal Analysis
Objective: This section uses a signal processing system to discuss important Simulink concepts such as multichannel frame-based systems, simulation from the command line, and defining system I/O. Following this section, students should be comfortable with how Simulink propagates signals and data during a simulation.
- Analyzing a signal
- Building an algorithm
- Frame-based processing
- Simulating models from the command line
- Multichannel signals
- Buffering
- Introducing noise
- Defining the system I/O using the Inport block
Filter
Objective: This section introduces the various tools and components that help users design filters in Simulink. We introduce these filter components and apply them on various noisy signals.
- Filtering library
- Digital filter block
- Filter architectures
- Digital filter design block and FDATool
- Filter realization wizard
- Filter Design Toolbox library
Multirate Systems
Objective: This section discusses the concept of multirate systems. A basic multirate model is used to illustrate multirate modeling features in Simulink. The section finishes with a case study of a digital audio rate converter.
- Multirate systems
- Discrete solvers
- Resampling
- Creating subsystems
- Aliasing and anti-aliasing filter
- Case study: digital audio rate converter
|
