DocumentCode
3186857
Title
The detection theory of self-organizing feature map and its application
Author
HuangFu Kan ; Wan Jian Wei
fYear
1992
fDate
18-22 May 1992
Firstpage
108
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
Keywords
edge detection; learning (artificial intelligence); neural nets; radar theory; self-organising feature maps; Kohonen; detection theory; edges; fuzziness; information processing; multidimensional detection; nonparametric detection; radar; self-organizing feature map; self-organizing learning; topological neighbors; Artificial neural networks; Associative memory; Biological neural networks; Gravity; Humans; Information processing; Neurons; Organizing; Probability distribution; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace and Electronics Conference, 1992. NAECON 1992., Proceedings of the IEEE 1992 National
Conference_Location
Dayton, OH
Print_ISBN
0-7803-0652-X
Type
conf
DOI
10.1109/NAECON.1992.220660
Filename
220660
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