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
Link To Document :
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