Signal Processing with Simulink

Day 1 of 3

What is Simulink?

Objective: Get an introduction to Simulink.

• System Design Process
• Model-Based Design with Simulink
• What Can You Do with Simulink?
• Simulink add-ons

Creating and Simulating a Model

Objective: Explore the Simulink interface and block libraries. Build a simple model and analyze the simulation results.

• Creating and editing a Simulink model
• Defining system inputs and outputs
• Simulating the model and analyzing results
• Performing automatic initialization of Simulink model parameters
• Visualizing signals with signal viewers

Modeling Discrete Dynamic Systems

Objective: Model discrete dynamic systems, and visualize frame-based signals and multichannel signals using a scope.

• Modeling a discrete system with basic blocks
• Finding sample times of block outputs
• Using frames in your model
• Using buffers
• Comparing frames vs. multichannel signals
• Viewing frame-based signals
• Understanding behavior of delay blocks with frame-based signals
• Working with multichannel frame-based signals

Modeling Logical Constructs

Objective: Model logical expressions. See how zero-crossing detection is used in Simulink and model simple logic in Simulink using MATLAB code.

• Modeling logical expressions
• Modeling conditional signal routing
• Understanding zero-crossing detection
• Modeling with the MATLAB Function block

From Algorithm to Model

Objective: Create a model from an algorithm specification.

• Modeling from algorithmic specifications
• Controlling model behavior under some error conditions
• Iterative algorithm development through modeling and simulation
• Verifying models against specified algorithms

Day 2 of 3

Mixed-Signal Models

Objective: Model mixed-signal systems.

• What is a mixed-signal model?
• Modeling an analog-to-digital Converter (ADC) with aperture jitter and nonlinearity
• Case study: Modeling TI's ADS62P29 ADC

Solver Selection

Objective: Choose the right solver for a Simulink model.

• Understanding the Simulink solver
• Solving simple models
• Solving models with discrete and continuous states
• Solving models with multiple rates
• Fixed-step and variable-step solvers
• Choosing a continuous-state system solver
• Handling zero crossings
• Handling algebraic loops

Subsystems and Libraries

Objective: Create custom blocks in Simulink, apply masks, and develop custom libraries.

• Creating subsystems
• Understanding virtual and atomic subsystems
• Using a subsystem as a model component
• Masking subsystems
• Creating custom block libraries
• Working with and modifying library blocks
• Adding custom libraries to the Simulink Library Browser

Conditional Subsystems

Objective: Model systems with parts that are executed conditionally.

• Modeling conditionally executed subsystems
• Creating enabled subsystems
• Creating triggered subsystems
• Working with an example using the AGC model

Spectral Analysis

Objective: Perform spectral analysis in the Simulink environment, and use spectrum computation in an algorithm.

• Performing spectral analysis with the Spectrum Analyzer block
• Choosing spectral analysis parameters
• Analyzing power spectrum of a fan motor noise
• Building a spectral classifier for speech
• Determining frequency response of a discrete system

Day 3 of 3

Designing and Applying Filters

Objective: Incorporate filters in a model, and explore different ways filters can be designed and implemented in a Simulink model.

• Designing filters in Simulink
• Modeling filters in fixed-point

Multirate Systems

Objective: Model multirate systems. Resample data and explore multirate filter blocks.

• Modeling multirate systems
• Exploring blocks for multirate signal processing
• Resampling oversampled data
• Designing and implementing anti-imaging and anti-aliasing filters
• Using multirate filter blocks
• Case study: Converting professional audio to CD format
• Converting the design to fixed point

Incorporating External Code

Objective: Import or incorporate custom or external MATLAB and C code into a Simulink model.

• Working with custom and external code
• Incorporating MATLAB code with the MATLAB Function block
• Incorporating C code with the C Caller block

Combining Models into Diagrams

Objective: Explore model integration, an important topic for large-scale projects in which several developers are developing different portions of a large system.

• Exploring model referencing and subsystems
• Setting up a model reference
• Setting up model reference arguments
• Exploring model reference simulation modes
• Viewing signals in referenced models
• Browsing model reference dependency graph

Automating Modeling Tasks

Objective: Control and run Simulink models from the MATLAB command line.

• Automating test runs
• Checking and modifying parameter settings
• Finding blocks with specific parameter values
• Constructing and modifying block diagrams