Simple Peak Detector

used for identifying peaks in time-series experimental data
Updated 29 Dec 2021
The detect_peaks algorithm uses rising and falling counters to assign a risingState with user-provided thresholds. Rising count is independent of falling count. A peak is detected when enough rising counts, then falling counts have successfully been detected.
The detect_peaks_with_rise algorithm is the same as detect_peaks except an additional constraint is added before detection. The total rise from the previous peak must be greater than a certain percentage of the total data range. This reduces chances of multiple unwanted repeated peaks. Drops in the data since the last detected peak is incorporated.
A simple Infinite Impulse Repsonse (IIR) filter is included and helpful with noisy data but not always necessary.
Four experimental datasets are provided that illlustrate both algorithms:
  1. sinuisoidal, or periodic
  2. constant but noisy data with 3 successive peaks
  3. rising, stair-step sequence A
  4. rising, stair-step sequence B
MATLAB Release Compatibility
Created with R2021a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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