Pattern detection in noisy signals

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.