matlab-extract-signal-features
Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a v
npx skills add matlab/matlab-agentic-toolkit --skill matlab-extract-signal-features --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.
# Extract Signal Features Per-frame feature extraction for 1D signals using the three Signal Processing Toolbox extractor objects. Picks the right extractor, configures it with real parameters only, and adds a GPU code path when one is available. ## When to Use - The user has a 1D signal and wants per-frame features for analysis or ML. - The user names specific features from any of the three extractor domains (time, frequency, time-frequency). - The user asks for a feature table or feature matrix to feed `fitcecoc`, `fitcnet`, or any classifier / regressor. - The user asks for per-frame statistics over a windowed signal. ## When NOT to Use - **Filter design or signal preprocessing** — out of scope. Filtering before feature extraction is a separate concern. - **Audio-specific features** (MFCC, mel-spectrogram, pitch, chroma, gammatone). Audio Toolbox's `audioFeatureExtractor` covers those — out of scope here. - **Batch / dataset orchestration** — `signalDatastore`, `labeledSignalSet`, `tall` arrays. The per-file extraction is in scope; building the pipeline around it is not. - **2D, image, or multivariate features** — out of scope by signal-type boundary. ## Workflow 0. **(Recommend
- When to Use
- When NOT to Use
- Workflow
- Choosing the right extractor
- Key Functions
- Patterns
- Time-domain features per frame
- Frequency-domain features with per-feature parameters
- Time-frequency features (spectrogram transform)
- GPU-accelerated extraction
- Post-extraction: aggregation and reproducibility
- Conventions (apply to all three extractors)
- Common cross-cutting pitfalls
- References
What does the matlab-extract-signal-features skill do?
Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a v
How do I install it?
Run `npx skills add matlab/matlab-agentic-toolkit --skill matlab-extract-signal-features --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.