Robust clustering methodology for multi-frequency acoustic data: A review of standardization, initialization and cluster geometry

Clustering is a useful unsupervised technique for the identification of acoustic groups in multi-frequency echograms based on frequency response. K-Means is the most well-known clustering technique but has significant requirements such as clusters of equal size and spherical shape. Initialization is a common problem in clustering as only local minima are usually guaranteed, and thus initialization must locate the centroids near the global...