DocumentCode :
296023
Title :
Self-organising learning of receptive fields in multi-resolution
Author :
Deng, D. ; Chan, K.P. ; Yu, Y.L.
Author_Institution :
Inst. of Radio Eng. & Autom., South China Univ. of Technol., Guangzhou, China
Volume :
5
fYear :
1995
fDate :
Nov/Dec 1995
Firstpage :
2831
Abstract :
The statistical likelihood of Gabor filters and primary visual cortex has been of interest for years, yet learning mechanisms proposed did not generate satisfactory Gabor-like receptive fields. In this paper, a new computational model of self-organised Hebbian learning (SOHL) is proposed to work on a multi-resolution image pyramid for the problem of visual receptive field learning. Receptive fields of both orientation and spatial frequency selectivity are observed in the authors´ simulation result
Keywords :
Hebbian learning; image resolution; physiological models; self-organising feature maps; spatial filters; visual perception; Gabor filters; multi-resolution image pyramid; primary visual cortex; receptive fields; self-organised Hebbian learning; statistical likelihood; visual receptive field learning; Biological system modeling; Brain modeling; Computational modeling; Computer science; Cost function; Gabor filters; Hebbian theory; Learning systems; Radio frequency; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.488182
Filename :
488182
Link To Document :
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