Prepare Signal Data

Look in Signal Processing Toolbox first. The conditioning, labeling, splitting, framing, and partitioning helpers here live in Signal Processing Toolbox — not in Stats & ML Toolbox or generic-MATLAB string utilities.

The arc: condition a raw signal (clean it) -> load a folder into a datastore -> label -> split / frame -> hand off to trainnet. Each stage is a workflow file; this page routes you to the right one.

When to Use

• Cleaning a single signal before analysis: fill gaps, remove drift, deoutlier, denoise, put it on a uniform time base, align multiple channels.
• Loading / preparing signal data for ML training: datastores, labels from filenames or folders, stratified splits, framing, parallel processing.
• Structured labeling: labeledSignalSet for Signal Labeler, all label types.

When NOT to Use