Please use this identifier to cite or link to this item: https://doi.org/10.1109/OCEANSAP.2006.4393920
Title: Wavelet de-noising with independent component analysis for segmentation of dolphin whistles in a noisy underwater environment
Authors: Seramani, S. 
Taylo, E.A.
Seekings, P.J. 
Yeo, K.P. 
Issue Date: 2007
Citation: Seramani, S.,Taylo, E.A.,Seekings, P.J.,Yeo, K.P. (2007). Wavelet de-noising with independent component analysis for segmentation of dolphin whistles in a noisy underwater environment. OCEANS 2006 - Asia Pacific : -. ScholarBank@NUS Repository. https://doi.org/10.1109/OCEANSAP.2006.4393920
Abstract: Bottlenose dolphins (Tursiops truncatus) are the most widely studied species of dolphin and are known to produce a complex mixture of different types of sounds. They are believed to communicate through frequency-modulated pure tones (whistles), and produce broadband clicks or click trains for echolocation while investigating their environment. They also produce a large range of other types of sounds variously described as barks, grunts, groans, etc. To further our aim of 2-way acoustically mediated communication with dolphins to study dolphin cognition, we need to separate Bottlenose dolphin whistles from noisy underwater recordings, which not only consist of whistles, but also broadband echolocation clicks, water splashes and other sources of ambient noise. Independent Component Analysis (ICA) has been successfully used for the separation of independent sound sources in many applications. In this paper we will discuss the use of ICA to separate dolphin whistles from other underwater sound sources. © 2006 IEEE.
Source Title: OCEANS 2006 - Asia Pacific
URI: http://scholarbank.nus.edu.sg/handle/10635/110947
ISBN: 1424401380
DOI: 10.1109/OCEANSAP.2006.4393920
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

1
checked on Nov 8, 2018

Page view(s)

31
checked on Oct 19, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.