Compression of Cuvier's beaked whale (Ziphius cavirostris) vocalizations using fast orthogonal search

This paper presents a compression algorithm that uses a non-linear modelling technique called fast orthogonal search (FOS) to create a functional expansion of the acoustic data. The candidate functions used in the functional expansion are transient signals that model Cuvier's beaked whale (Ziphius cavirostris) clicks as well as sinusoidal functions for modelling whale songs. A compression ratio of 93 is achieved by transmitting candidate identification numbers and weights for only the candidate functions that are chosen by the FOS algorithm. The acoustic signal is recreated using the weights and candidate numbers transmitted. The reconstructed time series is used as an input to a band-limited energy detector for whale vocalizations. The raw data and the reconstructed data have comparable probability of detection and missed detections, with fewer false alarms for the reconstructed signal.