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
Adaptive, Multirate, and Specialized Filter Design Methods
DSP System Toolbox provides many methods for designing and implementing digital filters. You can design filters with lowpass, highpass, bandpass, bandstop, and other response types and realize them using filter structures such as direct-form FIR, overlap-add FIR, direct-form II with second-order sections, cascade allpass, and lattice structures.
You can design filters in several ways: at the MATLAB command line, interactively using FDA Tool or Filterbuilder, or in Simulink using the filter design block library.
The system toolbox supports a number of design methods, including:
Advanced equiripple FIR filters, including minimum-order, constrained-ripple, minimum-phase designs
Nyquist and halfband FIR and IIR filters, providing linear phase, minimum-phase, and quasi-linear phase (IIR) designs, as well as equiripple, sloped-stopband, and window methods
Optimized multistage designs, enabling you to optimize the number of cascaded stages to achieve the lowest computational complexity
Fractional-delay filters, including implementation using Farrow filter structures well-suited for tunable filtering applications
Allpass IIR filters with arbitrary group delay, enabling you to compensate for the group delays of other IIR filters to obtain an approximate linear phase passband response
Lattice wave digital IIR filters, for robust fixed-point implementation
Arbitrary magnitude and phase FIR and IIR filters, enabling design of any filter specification
Specialized filter designs in MATLAB showing LMS adaptive filter applied to a noisy music signal (top left), arbitrary magnitude filter design (top right), direct-form FIR filter responses for fixed-point data types (bottom left), and octave filter design (bottom right).
Adaptive Filters
DSP System Toolbox provides several techniques for the design of adaptive filters: LMS-based, RLS-based, affine projection, fast transversal, frequency-domain, and lattice-based. The system toolbox also includes algorithms for the analysis of these filters, including tracking of coefficients, learning curves, and convergence.
Multirate Filters
DSP System Toolbox provides functions for the design and implementation of multirate filters, including polyphase interpolators, decimators, sample-rate converters, and CIC filters and compensators, as well as support for multistage design methods. The system toolbox also provides specialized analysis functions to estimate the computational complexity of multirate filters.
Interactive design of a lowpass filter in the Filterbuilder tool (left) and visualization of magnitude response (right).
Specialized Filters for DSP Applications
DSP System Toolbox lets you design and implement specialized digital filters, including:
- Audio weighting filters, octave filters, and parametric equalizer filters for audio, speech, and acoustic applications
- Pulse shaping, peak or notch, and multirate filters for communications systems
- Kalman filters for aerospace and navigation systems
Using Filters in Simulink System Models
The digital filters you design in DSP System Toolbox can also be used in system-level models in Simulink. MATLAB functions and System objects™ enable you to generate bit-true Simulink models from MATLAB filter designs. You can also use filter design block libraries in DSP System Toolbox to design, simulate, and implement filters directly in Simulink.
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