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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51474

Title: The Application of the Robust Discrete Wavelet Transform to Recursive Density Estimation
Authors: Shun-Hsyung Chang
Fu-Tai Wang
Contributors: 國立臺灣海洋大學:電機工程學系
Date: 2003-06
Issue Date: 2018-11-30T06:45:52Z
Publisher: International Journal of Electronics
Abstract: Abstract: This paper applies the notion of robust discrete wavelet transform (robust DWT) to recursive density estimation as a solution to detecting multipath signals underwater. Though there are no obvious distribution assumptions that can be made to model underwater noise, a recursive density estimator of the initial background noise reconstructed by the discrete wavelet transform (DWT) can be established as an empirical model. Observations that are identified as an outlier are then flagged as potential signals. In a multipath environment, where many signal components arrive with arbitrary delays, the DWT's lack of translation invariance is a problem for processing multipath signals. We adopt a robust DWT as a solution. Using an iterative algorithm in the Zak domain, a scaling function can be turned to a robust one. By designing a robust scaling function we can obtain a robust DWT. The performance of the robust DWT, exhibiting much better shift invariance than the conventional DWT, is illustrated. Utilizing the robust DWT reconstruction to establish the recursive density estimator of the underwater background noise, the ability to detect a multipath signal in an underwater environment is improved compared to that of the conventional DWT.
Relation: 90(6) pp.361-371
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/51474
Appears in Collections:[電機工程學系] 期刊論文

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