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An Analog VLSI Pulsed Neural Network Implementation for Image Segmentation
Dresden, Germany September 07-September 10
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PCEE.2004.11International Conference on Parallel ...
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Daniel Matolin, Dresden University of Technology, Germany
J? Schreiter, Dresden University of Technology, Germany
Stefan Getzlaff, Dresden University of Technology, Germany
Ren? Sch?, Dresden University of Technology, Germany
We present a massively parallel VLSI realisation of a pulse-coupled neural network for image segmentation. The network consists of simple integrate-and-fire (IAF) neurons with self-organising local connections. The prototype implementation comprises 64 x 64 neurons with coupling of four nearest neighbours, digital to analog converters, analog memories and a digital readout circuit. The chip has been fabricated in a 0.35μm standard CMOS technology.
Citation:
Daniel Matolin, J? Schreiter, Stefan Getzlaff, Ren? Sch?, "An Analog VLSI Pulsed Neural Network Implementation for Image Segmentation," parelec, pp.51-55, International Conference on Parallel Computing in Electrical Engineering, (PARELEC'04), 2004
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