Efficient method of automatic feature extraction and target classification

Yanning Zhang; Licheng Jiao

Efficient method of automatic feature extraction and target classification

Yanning Zhang
, Licheng Jiao

Xidian University

Research output: Contribution to journal › Conference article › peer-review

Abstract

P.R. China's fishery and offshore petroleum development have been in urgent need of a classifier of noise signals. In this paper, the feature extraction mechanism and the classification mechanism of the adaptive wavelet neural network are revealed by mathematical analysis, and an efficient engineering classifier based on the adaptive wavelet neural network is designed and applied to classify the actual ship noises. The classification experiment results show that the mathematical analysis of the feature extraction mechanism and the classification mechanism is correct and provides theoretical bases for the adaptive wavelet neural network classifier design.

Original language	English
Pages (from-to)	179-182
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	3
State	Published - 1998
Externally published	Yes
Event	Proceedings of the 1998 IEEE International Symposium on Circuits and Systems, ISCAS. Part 5 (of 6) - Monterey, CA, USA Duration: 31 May 1998 → 3 Jun 1998

Cite this

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title = "Efficient method of automatic feature extraction and target classification",

abstract = "P.R. China's fishery and offshore petroleum development have been in urgent need of a classifier of noise signals. In this paper, the feature extraction mechanism and the classification mechanism of the adaptive wavelet neural network are revealed by mathematical analysis, and an efficient engineering classifier based on the adaptive wavelet neural network is designed and applied to classify the actual ship noises. The classification experiment results show that the mathematical analysis of the feature extraction mechanism and the classification mechanism is correct and provides theoretical bases for the adaptive wavelet neural network classifier design.",

author = "Yanning Zhang and Licheng Jiao",

year = "1998",

language = "英语",

volume = "3",

pages = "179--182",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 1998 IEEE International Symposium on Circuits and Systems, ISCAS. Part 5 (of 6) ; Conference date: 31-05-1998 Through 03-06-1998",

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AU - Zhang, Yanning

AU - Jiao, Licheng

PY - 1998

Y1 - 1998

N2 - P.R. China's fishery and offshore petroleum development have been in urgent need of a classifier of noise signals. In this paper, the feature extraction mechanism and the classification mechanism of the adaptive wavelet neural network are revealed by mathematical analysis, and an efficient engineering classifier based on the adaptive wavelet neural network is designed and applied to classify the actual ship noises. The classification experiment results show that the mathematical analysis of the feature extraction mechanism and the classification mechanism is correct and provides theoretical bases for the adaptive wavelet neural network classifier design.

AB - P.R. China's fishery and offshore petroleum development have been in urgent need of a classifier of noise signals. In this paper, the feature extraction mechanism and the classification mechanism of the adaptive wavelet neural network are revealed by mathematical analysis, and an efficient engineering classifier based on the adaptive wavelet neural network is designed and applied to classify the actual ship noises. The classification experiment results show that the mathematical analysis of the feature extraction mechanism and the classification mechanism is correct and provides theoretical bases for the adaptive wavelet neural network classifier design.

UR - https://www.scopus.com/pages/publications/0031628180

M3 - 会议文章

AN - SCOPUS:0031628180

SN - 0271-4310

VL - 3

SP - 179

EP - 182

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - Proceedings of the 1998 IEEE International Symposium on Circuits and Systems, ISCAS. Part 5 (of 6)

Y2 - 31 May 1998 through 3 June 1998

ER -

Efficient method of automatic feature extraction and target classification

Abstract

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