DSP Blockset

Simulink block libraries for the design, simulation, and prototyping of digital signal processing systems

The DSP Blockset provides an intuitive graphical tool for the rapid design, simulation, and prototyping of digital signal processing systems. It contains more than 100 blocks for creating and analyzing DSP designs. Together with MATLAB and Simulink, the DSP Blockset simplifies DSP system design by integrating algorithm development, simulation, and real-time implementation.

The DSP Blockset Version 2.0 is a major upgrade to the DSP Blockset. This release includes a number of new libraries and blocks that enhance the ability to model both discrete-time and hybrid systems, including support for adaptive and multirate filtering, a matrix math library, signal processing blocks for time and frequency-domain modeling, spectral analysis blocks and new building blocks such as switches and counters.

These new blocks extend the application of Simulink for use in the design, simulation, and prototyping of digital signal processing (DSP) in devices and systems such as wire-based and mobile communications, computer peripherals, speech and audio processing, automotive controls, and medical diagnostics.

Features

The DSP Blockset provides signal processing functions including FFT, inverse FFT, filters, buffer, and unbuffer. New blocks include switches and counters. Support is now available for up/down sampling and enhanced window options.
Complex math and signal operations include magnitude, phase, conjugate, mux, and demux.
Vector math and statistics blocks are now available to provide faster computations and improved handling and processing of complex - valued signals.
The filter library has been expanded and refined to include adaptive and multirate filtering, with enhanced usability of FIR, IIR, and other filter design blocks.
Signal processing blocks for time- and frequency-domain modeling are available.
The matrix math library complements existing vector-based simulation capabilities to advance algorithm development.
Spectral analysis blocks consist of Welch's method and additional scope blocks.
The "true libraries" new feature makes dynamic linking, updating, and sharing of blocks easy.
Real-Time Workshop provides portable C code generation for programmable floating-point DSPs.

Highlights

Block Diagram DSP Simulation. The DSP Blockset complements the powerful algorithm development and signal analysis tools in MATLAB by providing an interactive block diagram DSP simulation environment. It also adds convenient handling of buffered data and complex signals to Simulink in order to support frame-based processing and DSP simulation.

Advanced Signal Processing Power. The DSP Blockset offers a wide range of built-in DSP techniques for spectral analysis and filter design. You can also add your own custom algorithms without low-level programming. Portable C Code Generation. The DSP Blockset interfaces seamlessly with Real-Time Workshop, allowing you to automatically generate real-time ANSI C code from your Simulink DSP simulations. This code generation facility lets you streamline prototyping and implementation on programmable floating-point DSP hardware.

Integrated, Open Environment. Simulink and the DSP Blockset extend the power of MATLAB to model, analyze, and visualize signals and DSP algorithms. Together they give you a single integrated environment that helps you speed up the development of DSP-based systems.

Additional Links

Read an article describing the new DSP Blockset functionality, entitled DSP Blockset Signals New Applications for Simulink.

Applications for the DSP Blockset include design and analysis of communications systems, computer peripherals, speech and audio processing, automotive and aerospace controls, and medical electronics. It is ideal for both time and frequency-domain algorithms, including problems such as adaptive noise cancellation.

A technical brief available from The MathWorks demonstrates how the Simulink DSP Blockset facilitates the simulation and design of DSP-based systems. It describes applications in power spectrum estimation, nonlinear dynamic range compression, and adaptive filtering.

To request your technical brief or DSP Blockset datasheet, please fill out and submit the MathWorks information request form.

Stefan Steinhaus, webmaster@steinhaus-net.de