DocumentCode :
2200304
Title :
Analog implementation for networks of integrate-and-fire neurons with adaptive local connectivity
Author :
Schreiter, Jörg ; Ramacher, Ulrich ; Heittmann, Arne ; Matolin, Daniel ; Schüffny, René
Author_Institution :
Dept. of Electr. Eng. & Inf. Technol., Dresden Univ. of Technol., Germany
fYear :
2002
fDate :
2002
Firstpage :
657
Lastpage :
666
Abstract :
An analog VLSI implementation for pulse coupled neural networks of leakage free integrate-and-fire neurons with adaptive connections is presented. Weight adaptation is based on existing adaptation rules for image segmentation. Although both integrate-and-fire neurons and adaptive weights can be implementation only approximately, simulations have shown, that synchronization properties of the original adaptation rules are preserved.
Keywords :
VLSI; analogue integrated circuits; image segmentation; neural chips; synchronisation; adaptation rules; adaptive connections; adaptive local connectivity; analog VLSI implementation; image segmentation; integrate-and-fire neurons; pulse coupled neural networks; simulations; synchronization properties; weight adaptation; Frequency synchronization; Hardware; Image segmentation; Information technology; Nearest neighbor searches; Neural networks; Neurons; Robustness; Signal processing; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on
Print_ISBN :
0-7803-7616-1
Type :
conf
DOI :
10.1109/NNSP.2002.1030077
Filename :
1030077
Link To Document :
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