DSP System Toolbox

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 using MATLAB functions, apps, or Simulink blocks.

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, arbitrary magnitude filter design, direct-form FIR filter responses for fixed-point data types, and octave filter design.
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 and visualization of magnitude response.
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.

Filter Design in MATLAB

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