matlab-design-adaptive-filter
Design and implement adaptive filters using DSP System Toolbox System objects. Use when working with adaptive filtering, system identification, noise cancellation, echo cancellation, active noise control (ANC), channel equalization, inverse system identification, or adaptive prediction. Covers dsp.LMSFilter, dsp.RLSFilter, dsp.FilteredXLMSFilter, dsp.FrequencyDomainAdaptiveFilter, dsp.AffineProjectionFilter, dsp.BlockLMSFilter, dsp.AdaptiveLatticeFilter, dsp.FastTransversalFilter, maxstep(), and algorithm selection for adaptive filtering problems. Replaces deprecated adaptfilt.* objects (remov
npx skills add matlab/matlab-agentic-toolkit --skill matlab-design-adaptive-filter --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Adaptive Filtering Implementation guideline — Use DSP System Toolbox System objects to implement adaptive filters. Do not implement manual weight-update loops. ## When to Use - System identification — Model unknown FIR or IIR systems online - Noise or interference cancellation — Recover signals from noise-corrupted measurement - Echo cancellation — Suppress acoustic or line echo - Active noise control — Feedforward ANC with secondary path - Inverse system identification — Equalization and deconvolution - Adaptive prediction — Linear prediction and speech coding - Algorithm evaluation — Compare adaptive filter algorithm performance - Migrating from deprecated `adaptfilt.*` objects — Replaced by `dsp.*Filter` System objects (removed in R2020a) - Any task involving `dsp.LMSFilter`, `dsp.RLSFilter`, `dsp.FilteredXLMSFilter`, `dsp.FrequencyDomainAdaptiveFilter`, `dsp.AffineProjectionFilter`, or `maxstep()` ## When NOT to Use - Static (non-adaptive) FIR/IIR filter design — Use `matlab-design-digital-filter` - Kalman filtering or state estimation — Use Control System Toolbox - Deep learning-based denoising — Use Deep Learning Toolbox - Simulink adaptive filter blocks — Use when working
- When to Use
- When NOT to Use
- Workflow
- 1. Analyze the Problem
- 2. Select Object and Method
- 3. Configure
- 4. Run in Streaming Loop
- 5. Verify Convergence and Extract Weights
- Key Functions
- Patterns
- System Identification
- Active Noise Control (Two-Stage)
- Low-Latency Long Filter (Partitioned FDAF)
- Freeze Adaptation (Stop Learning, Keep Filtering)
What does the matlab-design-adaptive-filter skill do?
Design and implement adaptive filters using DSP System Toolbox System objects. Use when working with adaptive filtering, system identification, noise cancellation, echo cancellation, active noise control (ANC), channel equalization, inverse system identification, or adaptive prediction. Covers dsp.LMSFilter, dsp.RLSFilter, dsp.FilteredXLMSFilter, dsp.FrequencyDomainAdaptiveFilter, dsp.AffineProjectionFilter, dsp.BlockLMSFilter, dsp.AdaptiveLatticeFilter, dsp.FastTransversalFilter, maxstep(), and algorithm selection for adaptive filtering problems. Replaces deprecated adaptfilt.* objects (remov
How do I install it?
Run `npx skills add matlab/matlab-agentic-toolkit --skill matlab-design-adaptive-filter --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From matlab/matlab-agentic-toolkit, a repository with 868 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.