NDLI: The detection theory of self-organizing feature map and its application

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The detection theory of self-organizing feature map and its application

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The detection theory of self-organizing feature map and its application

Content Provider	IEEE Xplore Digital Library
Author	Wu Yan Yan Huangfu Kan Zhou Liangzhu Wan Jian Wei
Copyright Year	1992
Description	Author affiliation: Dept. of Electron. Tech., Changsha Inst. of Technol., Hunan, China (Wu Yan Yan; Huangfu Kan; Zhou Liangzhu; Wan Jian Wei)
Abstract	Artificial neural network models have previously been studied in the hope of achieving human-like performance in the field of information processing. The optimized learning rule, based on the Kohonen self-organizing feature map, is modified in order to decrease the fuzziness on the edges of the topological neighbors. The authors describe the mathematical mechanisms of multidimensional detection, and its application in a radar system. High-accuracy performance is achieved, and detection is nonparametric because of the self-organizing learning process.<>
Starting Page	108
Ending Page	112
File Size	295049
Page Count	5
File Format	PDF
ISBN	078030652X
DOI	10.1109/NAECON.1992.220660
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1992-05-18
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gravity Biological neural networks Humans Information processing Associative memory Stochastic processes Artificial neural networks Organizing Neurons Probability distribution
Content Type	Text
Resource Type	Article

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