title: Implementation of a pulse coupled neural network in FPGA.
abstract: The Pulse Coupled neural network, PCNN, is a biologically inspired neural net and it can be used in various image analysis applications, e.g. time-critical applications in the field of image pre-processing like segmentation, filtering, etc. a VHDL implementation of the PCNN targeting FPGA was undertaken and the results presented here. The implementation contains many interesting features. By pipelining the PCNN structure a very high throughput of 55 million neuron iterations per second could be achieved. By making the coefficients re-configurable during operation, a complete recognition system could be implemented on one, or maybe two, chip(s). Reconsidering the ranges and resolutions of the constants may save a lot of hardware, since the higher resolution requires larger multipliers, adders, memories etc.
authors.affiliation: Optronic Consult i Norden AB, Skellefteå, Sweden.
authors.forename: J
authors.initials: J
authors.lastname: Waldemark
authors.forename: M
authors.initials: M
authors.lastname: Millberg
authors.forename: T
authors.initials: T
authors.lastname: Lindblad
authors.forename: K
authors.initials: K
authors.lastname: Waldemark
authors.forename: V
authors.initials: V
authors.lastname: Becanovic
mesh_terms: D000703:Analog-Digital Conversion; D003201:Computers; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008328:Man-Machine Systems; D016571:Neural Networks, Computer