A Study on Parallel RKAM for Raster FCNN Simulation

This paper addresses the raster fuzzy cellular neural network simulation for any kind as well as any size of input image using parallel arithmetic and geometric mean algorithms of type-1 and type-2 (2-parallel 2-processor 2-stage 3-order) by an efficient program fragment in order to exploit its late...

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Bibliographic Details
Published inJournal of Computer Science and Control Systems Vol. 4; no. 2; p. 63
Main Authors SUKUMAR, Senthilkumar, Mt Piah, Abd Rahni
Format Journal Article
LanguageEnglish
Published Oradea University of Oradea 01.10.2011
Subjects
Algorithms
Arithmetic
Computer simulation
Control systems
Fuzzy logic
Integration
Neural networks
Raster
Simulation
Studies
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Summary:This paper addresses the raster fuzzy cellular neural network simulation for any kind as well as any size of input image using parallel arithmetic and geometric mean algorithms of type-1 and type-2 (2-parallel 2-processor 2-stage 3-order) by an efficient program fragment in order to exploit its latency properties effectively. Significant simulation outputs are displayed with respect to the methods and paradigm. [PUBLICATION ABSTRACT]
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:1844-6043
2067-2101