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matlab-design-adaptive-filter

Design and implement adaptive filters using DSP System Toolbox System objects in MATLAB.

995|122|Updated Apr 3, 2026
Search Tags:#RLS#echo cancellation#lms#matlab#dsp system toolbox#adaptive filter#active noise control
One-click install
npx skills add https://github.com/matlab/matlab-agentic-toolkit --skill matlab-design-adaptive-filter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: matlab-design-adaptive-filter
Source: https://github.com/matlab/matlab-agentic-toolkit/tree/main/skills-catalog/signal-processing/matlab-design-adaptive-filter
Command: npx skills add https://github.com/matlab/matlab-agentic-toolkit --skill matlab-design-adaptive-filter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Choosing the right adaptive filter algorithm, configuring stable step sizes, and extracting converged weights in MATLAB are error-prone tasks, especially since the deprecated adaptfilt.* package was removed in R2020a and each dsp.*Filter object exposes weights differently.

Core Features & Use Cases

  • Algorithm Selection: Route system identification, noise cancellation, echo cancellation, active noise control, equalization, and prediction tasks to the correct System object (LMS, RLS, FxLMS, FDAF, Affine Projection, Block LMS, Lattice, Fast Transversal).
  • Stability and Convergence Guidance: Use maxstep() where supported, tune ForgettingFactor for RLS, and avoid divergence pitfalls such as sign-based LMS with zero initial weights.
  • Correct Weight Extraction: Access coefficients per object, including third-output extraction for dsp.LMSFilter and FFTCoefficients plus IFFT for partitioned FDAF.
  • Use Case: Build a real-time acoustic echo canceller with a 2048-tap partitioned constrained FDAF at 8 ms latency, or a two-stage active noise control system using dsp.FilteredXLMSFilter with an estimated secondary path.

Quick Start

Ask your agent to design an adaptive filter for system identification of an unknown FIR system using dsp.LMSFilter with a stable step size from maxstep.

Frequently Asked Questions about matlab-design-adaptive-filter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement an adaptive filter in MATLAB?▼

Use DSP System Toolbox System objects such as dsp.LMSFilter or dsp.RLSFilter rather than manual weight-update loops. Configure the filter length and method, set a stable step size with maxstep where supported, then process data frame-by-frame in a streaming loop.

Which adaptive filter algorithm should I use for my application?▼

Use Normalized LMS for general-purpose tasks, RLS for fast convergence or tracking time-varying systems, Affine Projection for colored inputs, Filtered-X LMS for active noise control, and Frequency-Domain Adaptive Filter for long filters over 256 taps.

What replaced adaptfilt in MATLAB?▼

The entire adaptfilt package was removed in R2020a. Replace adaptfilt.lms with dsp.LMSFilter, adaptfilt.rls with dsp.RLSFilter, and similar adaptfilt objects with the corresponding dsp.*Filter System objects.

Why does dsp.LMSFilter not have a Coefficients property?▼

dsp.LMSFilter returns adapted weights only through its third output argument, as in [y, e, w] = lms(x, d). Accessing .Coefficients throws an unrecognized property error; the same applies to dsp.BlockLMSFilter and dsp.FrequencyDomainAdaptiveFilter.

How do I reduce latency for long adaptive filters in MATLAB?▼

Use dsp.FrequencyDomainAdaptiveFilter with the Partitioned constrained FDAF method and a small BlockLength. Latency equals BlockLength divided by the sample rate, so a 2048-tap filter with BlockLength 128 at 16 kHz achieves 8 ms latency.

Why does my sign-based LMS filter never converge?▼

Sign-Data and Sign-Sign LMS stall with zero initial weights because sign(0) equals zero, producing no update. Set InitialConditions to small nonzero values and tune StepSize empirically, since maxstep is not supported for these methods.

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