In this paper is presented the use of the discrete-time cellular neural network (DTCNN) paradigm to develop algorithms devised for general-purpose massively parallel processing (MPP) systems. This paradigm is defined in discrete N-dimensional spaces (lattices) and is characterized by the locality of
Hopfield neural network simulation on a massively parallel machine
β Scribed by Max J. Domeika; Edward W. Page
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 546 KB
- Volume
- 91
- Category
- Article
- ISSN
- 0020-0255
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