Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Segmentation of Killer Whale Vocalizations Using the Hilbert-Huang Transform | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 245936 10 pages doi 2008 245936 Research Article Segmentation of Killer Whale Vocalizations Using the Hilbert-Huang Transform Olivier Adam Laboratorie d Images Signaux et Systemes Intelligents LiSSi - iSnS Universite de Paris 12 61 avenue de Gaulle 94010 Creteil Cedex France Correspondence should be addressed to Olivier Adam adam@ Received 1 September 2007 Revised 3 March 2008 Accepted 14 April 2008 Recommended by Daniel Bentil The study of cetacean vocalizations is usually based on spectrogram analysis. The feature extraction is obtained from 2D methods like the edge detection algorithm. Difficulties appear when signal-to-noise ratios are weak or when more than one vocalization is simultaneously emitted. This is the case for acoustic observations in a natural environment and especially for the killer whales which swim in groups. To resolve this problem we propose the use of the Hilbert-Huang transform. First we illustrate how few modes 5 are satisfactory for the analysis of these calls. Then we detail our approach which consists of combining the modes for extracting the time-varying frequencies of the vocalizations. This combination takes advantage of one of the empirical mode decomposition properties which is that the successive IMFs represent the original data broken down into frequency components from highest to lowest frequency. To evaluate the performance our method is first applied on the simulated chirp signals. This approach allows us to link one chirp to one mode. Then we apply it on real signals emitted by killer whales. The results confirm that this method is a favorable alternative for the automatic extraction of killer whale vocalizations. Copyright 2008 Olivier Adam. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any .
