DSP System Toolbox
Product Description
- Introduction and Key Features
- DSP Algorithms for System Design and Prototyping
- Adaptive, Multirate, and Specialized Filter Design Methods
- Streaming and Frame-Based Signal Processing
- Signal Generation, I/O, and Visualization
- Fixed-Point Implementation and Code Generation for DSP System Models
Streaming and Frame-Based Signal Processing
DSP System Toolbox enables the efficient simulation of real-time signal processing systems by supporting streaming signal processing and frame-based processing in MATLAB and Simulink.
Streaming and frame-based processing techniques accelerate simulations by buffering input data into frames and processing multiple samples of data at a time. Faster simulations are achieved due to the distribution of the fixed process overhead across many samples. Although these techniques introduce a certain amount of latency in the system, in many instances you can select frame sizes that improve throughput without creating unacceptable latencies.
In MATLAB, streaming signal processing is enabled by using System objects™ to represent data-driven algorithms, sources, and sinks. System objects implicitly manage many details of stream processing, such as data indexing, buffering, and algorithm state management. You can mix System objects with standard MATLAB functions and operators. MATLAB programs that use System objects can be incorporated into Simulink models via the MATLAB Function block. Most System objects have corresponding Simulink blocks with the same capabilities.
In Simulink, DSP System Toolbox blocks process input signals as frames when the specified input processing mode on the block dialog is set to frame-based processing. DSP System Toolbox supports sample-based processing for low latency processes and for applications that require scalar processing. Many blocks support both sample-based and frame-based processing modes.
