DocumentCode :
1907855
Title :
An extended self-organizing map with gated neurons
Author :
Chandrasekaran, V. ; Palaniswami, M. ; Caelli, Terry M.
Author_Institution :
Sch. of Inf. Technol. & Electr. Eng., Melbourne Univ., Parkville, Vic., Australia
fYear :
1993
fDate :
1993
Firstpage :
1474
Abstract :
Kohonen´s self-organizing map is extended by a technique allowing the neurons in the feature map to compete in a selective manner. This is accomplished by introducing gated neurons prior to the winner-take-all layer. These gated neurons are activated by a cosine function with time-varying frequency. This results in a spatio-temporal signature at the output for each input pattern over a predetermined interval. This pattern is found to be unique in its characteristics and leads to very high degree of recognition results. The simulations performed on a standard texture recognition problem indicate excellent performance
Keywords :
image recognition; self-organising feature maps; vector quantisation; Kohonen´s self-organizing map; cosine function; feature map; gated neurons; spatio-temporal signature; texture recognition; time-varying frequency; winner-take-all layer; Computer architecture; Frequency; Information technology; Neural networks; Neurons; Pattern classification; Pattern recognition; Self organizing feature maps; Signal processing; Supervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
Type :
conf
DOI :
10.1109/ICNN.1993.298774
Filename :
298774
Link To Document :
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