Paper
22 March 1999 Generic VHDL implementation of a PCNN with loadable coefficients
Mikael Millberg, Johnny Oberg, Joakim T. A. Waldemark
Author Affiliations +
Proceedings Volume 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks; (1999) https://doi.org/10.1117/12.343037
Event: Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, 1998, Stockholm, Sweden
Abstract
This paper presents a general VHDL implementation of a Pulse Coupled Neural Network. The VHDL implementation is targeted for FPGA but can also be used with advantage for ASIC implementations. This particular case deals with images of the size 128 X 128 pixels coming at a rate of 60 images per second, each image iterated by the PCNN 70 times, i.e. a real time image processing system. Thanks to the generality, this suggested solution can easily be transformed into, e.g., a solution with images sized 32 X 32 pixels, coming at a speed of 960 images per second, assuming the same iteration length. The hardware requirement and problems are analyzed and solutions are proposed. Some problems that are dealt with are: the huge amount of data produced, the high throughput (i.e. the rate of new data produced) and the loading of coefficients during runtime.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mikael Millberg, Johnny Oberg, and Joakim T. A. Waldemark "Generic VHDL implementation of a PCNN with loadable coefficients", Proc. SPIE 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); https://doi.org/10.1117/12.343037
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Neurons

Field programmable gate arrays

Image segmentation

Neural networks

Clocks

Data storage

Image fusion

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