Pattern detection in noisy signals

Markus Christen, Albert Kern, J.-J. van der Vyver, Ralph Lukas Stoop · 2004

Methods for detecting patterns in noisy signals are often template based. As a consequence, a priori selections of potential pattern structures have to be made. To avoid this shortcoming, we propose a novel statistical approach based on the correlation integral. The method significantly reduces the set of appropriate templates, and also works under noisy conditions.

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