An Efficient Algorithm for Automatic Peak Detection in Noisy Periodic and Quasi-Periodic Signals - Top 10 Cited Papers in Algorithms journal

Top 10 Cited Papers in Algorithms journal

Felix Scholkmann * , Jens Boss and Martin Wolf

Biomedical Optics Research Laboratory, Division of Neonatology, University Hospital Zurich, 8091 Zurich, Switzerland

*Author to whom correspondence should be addressed.

Received: 3 August 2012 / Revised: 29 October 2012 / Accepted: 13 November 2012 / Published: 21 November 2012

Abstract

We present a new method for automatic detection of peaks in noisy periodic and quasi-periodic signals. The new method, called automatic multiscale-based peak detection (AMPD), is based on the calculation and analysis of the local maxima scalogram, a matrix comprising the scale-dependent occurrences of local maxima. The usefulness of the proposed method is shown by applying the AMPD algorithm to simulated and real-world signals. View Full-Text

Keywords: peak detection; local maxima scalogram; multiscale local maxima detection; automatic multiscale-based peak detection (AMPD) algorithm