Objective: Get an introduction to Simulink.

• What is Simulink?
• Benefits of using Simulink
• Simulink add-ons
• A look at a Simulink 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

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
• Frames vs. multichannel signals
• Viewing frame-based signals
• Behavior of delay blocks with frame-based signals
• Multichannel frame-based signals

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

Objective: Create a model from an algorithm specification.

• Modeling from algorithmic specifications
• Iterative algorithm development through modeling and simulation
• Verifying models against specified algorithms

Objective: Model mixed-signal systems.

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

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

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
• Creating configurable subsystems

Objective: Model systems with parts that are executed conditionally.

• Conditionally executed subsystems
• Modeling condition-driven systems with enabled subsystems
• Modeling condition-driven systems with triggered subsystems
• Working with an example using the AGC model

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

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

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

• Designing filters in Simulink
• Converting filters to fixed point

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

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

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

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 the model reference dependency graph

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