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