DSP System Toolbox
Design and simulate streaming signal processing systems
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DSP System Toolbox provides algorithms, apps, and scopes for designing, simulating, and analyzing signal processing systems in MATLAB and Simulink. You can model real-time DSP systems for communications, radar, audio, medical devices, IoT, and other applications.
With DSP System Toolbox you can design and analyze FIR, IIR, multirate, multistage, and adaptive filters. You can stream signals from variables, data files, and network devices for system development and verification. The Time Scope, Spectrum Analyzer, and Logic Analyzer let you dynamically visualize and measure streaming signals. For desktop prototyping and deployment to embedded processors, including ARM® Cortex® architectures, the system toolbox supports C/C++ code generation. It also supports bit-accurate fixed-point modeling and HDL code generation from filters and other algorithms.
Algorithms are available as MATLAB functions, System objects, and Simulink blocks.
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DSP System Toolbox offers blocks for algorithms, filters, transforms, and linear algebra. Apply frame-based processing for higher throughput and more accurate modeling of real-time systems, or multirate filters to simulate different sample rates.
Use the Filter Builder app and Filter Designer to design and implement FIR, IIR, multistage, multirate, and adaptive filters. Design based on frequency selectivity criteria or via optimization-driven algorithms. Use the Filter Analyzer app to compare filter responses.
Design: Documentation | Examples
Implementation: Documentation | Examples
Visualize signal data in the time or frequency domain with Scopes. Similar to established benchtop signal analyzers, scopes provide measurements and statistics to analyze your data. Use Spectrum Analyzer to display spectrum and spectrogram views.
Transform signals between the time and frequency domains. Use blocks to implement parametric or non-parametric estimation, and evaluate streaming signal statistics.
Generate source code to accelerate, prototype, and deploy signal processing algorithms with MATLAB Coder and Simulink Coder. Use Embedded Coder to generate optimized software through core-specific libraries and SIMD implementations.
Use AI-powered signal processing algorithms in Simulink. Detect anomalies in signals using deep learning models and extract deep signal features using Wavelet Scattering.
DSP System Toolbox provides algorithms, apps, and scopes for designing, simulating, and analyzing signal processing systems in MATLAB and Simulink for applications including communications, radar, audio, medical devices, and IoT.
You can design and analyze FIR, IIR, multirate, multistage, and adaptive filters using the Filter Designer app based on frequency selectivity criteria or optimization-driven algorithms. The toolbox also allows simulating dynamic filter architectures through time-tunable design algorithms, coefficient-tunable implementations, and dynamic response analysis. It includes efficient filter implementation architectures, such as frequency-domain and MIMO FIR filter implementations.
The toolbox includes Time Scope, Spectrum Analyzer, Dynamic Filter Visualizer and Logic Analyzer that let you dynamically visualize and measure streaming signals, providing measurements and statistics similar to benchtop signal analyzers.
Yes, the toolbox supports C/C++ code generation for desktop prototyping and deployment to embedded processors, including ARM Cortex architectures, as well as bit-accurate fixed-point modeling and HDL code generation.
Algorithms are available as MATLAB functions, System objects, and Simulink blocks.
Yes – the toolbox provides design algorithms and implementation modules for multirate filters across MATLAB and Simulink. The availability of, multirate filter blocks in Simulink enables the use of different discrete sample rates in the simulation of signal processing systems, for higher throughput and more accurate modeling of real-time systems.
Yes – the availability of signal processing algorithms as MATLAB System objects and Simulink blocks allows processing signals streamed from variables, data files, and network devices without additional or manual handling of the internal states of the algorithms.
Yes, the toolbox includes AI-powered signal processing algorithms in Simulink for detecting anomalies in signals using deep learning models and extracting deep signal features using Wavelet Scattering.
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