alexa Haar Wavelet Method to Spectral Analysis Continuous Wav
ISSN: 2168-9679

Journal of Applied & Computational Mathematics
Open Access

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Research Article

Haar Wavelet Method to Spectral Analysis Continuous Wavelet Transform 1D Using Whistle Sound to Position of Dolphins (Tursiops aduncus)

Lubis MZ*, Pujiyati S, Hestirianoto T and Wulandari PD

Department of Marine Science and Technology, Bogor Agricultural University Jln. Agatis, Indonesia

*Corresponding Author:
Lubis MZ
Department of Marine Science and Technology
Bogor Agricultural University Jln. Agatis
Kampus IPB, Dramaga Bogor, 16680 Indonesia
Tel: +622518622642
E-mail: [email protected]

Received April 27, 2016; Accepted May 16, 2016; Published May 20, 2016

Citation: Lubis MZ, Pujiyati S, Hestirianoto T, Wulandari PD (2016) Haar Wavelet Method to Spectral Analysis Continuous Wavelet Transform 1D Using Whistle Sound to Position of Dolphins (Tursiops aduncus). J Appl Computat Math 5:305. doi: 10.4172/2168-9679.1000305

Copyright: © 2016 Lubis MZ, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



In wavelet method have a wavelet transform is a signal processing technique was developed as a method to obtain simultaneous, have high resolution frequency and time. Mother wavelet have one method with namely haar wavelet, haar wavelet had become an effective tool for solving many problems arising in many branches of sciences. Haar wavelet functions have been used since year at 1910. It was introduced by the Hungarian mathematician Alfred Haar. This article discuss about signal processing with haar wavelet (continuous wavelet transform) using whistle sound and position of dolphins. Results of modulus of Ca, b Coefficients-Coloration init mode + scale, demonstrating the maximum yield that is in the frequency of 4.1 kHz-5.9 kHz with the brightest colors, and need for the process of de-noising 1D to a level that is more, such as level 10. In this article indicates a change in position dolphins to signal that it generates, and proved this by using the haar wavelet analysis on a dependent threshold level. haar wavelet analysis on a dependent threshold level. Retained energy is 65, 87%-zeros 87, 01% in original and compressed signal with haar wavelet using dolphins whistle sound, Equations or methods used in this article is very effective to remove noise from whistle sound of dolphins.


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