Digital implementation of artificial neural networks / Saffih Faycal

This thesis is concerned with the philosophy and the strategies related to the digital implementations of artificial neural networks ANN. An open and deep insight of the biological origin of ANN as well as its tidy relation with physics through statistical mechanics and the Hopficld revolutionary co...

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Main Author: Saffih , Faycal
Format: Thesis
Published: 1998
Subjects:
Online Access:http://studentsrepo.um.edu.my/15239/1/Saffih_Faycal.pdf
http://studentsrepo.um.edu.my/15239/
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author Saffih , Faycal
author_facet Saffih , Faycal
author_sort Saffih , Faycal
building UM Library
collection Institutional Repository
content_provider Universiti Malaya
content_source UM Student Repository
continent Asia
country Malaysia
description This thesis is concerned with the philosophy and the strategies related to the digital implementations of artificial neural networks ANN. An open and deep insight of the biological origin of ANN as well as its tidy relation with physics through statistical mechanics and the Hopficld revolutionary concept of computational energy (See Ref (4] of Chapter 2) is given. The Very Large-Scale Integration VLSI implementation of ANN (mainly digital) with its diverse methodologies, strategies and goals also discussed. The notion of parallelism that was the comer stone of the third chapter in the processing (or the hardware) point-of-view and is enhanced in the fourth chapter to introduce the parallel learning-processing PLP notion. The Printed Circuit Board PCB technique is applied for the implementation of PLP-based neuron Bidirectional Associative Memory BAM using the cad tool of EEDIII that simulates it and shows the technique limited capabilities. The powerful Very Hardware Description Language VHDL is introduced and used to implement more suitable versions of the previous circuit and other, to be downloaded on a Field Programmable Gate Arrays FPGA chips. The PLP neuron-based BAM implementation is enhanced further by the introduction of the encodingcomparing technique as a user interface with the network as well as the expandability technique based on the suggested systolic-like architecture. Finally. the bus-based architecture technique is presented for the implementation of the Hopfield ANN.
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publishDate 1998
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spelling my.um.stud-152392024-05-29T19:00:31Z Digital implementation of artificial neural networks / Saffih Faycal Saffih , Faycal Q Science (General) QA75 Electronic computers. Computer science This thesis is concerned with the philosophy and the strategies related to the digital implementations of artificial neural networks ANN. An open and deep insight of the biological origin of ANN as well as its tidy relation with physics through statistical mechanics and the Hopficld revolutionary concept of computational energy (See Ref (4] of Chapter 2) is given. The Very Large-Scale Integration VLSI implementation of ANN (mainly digital) with its diverse methodologies, strategies and goals also discussed. The notion of parallelism that was the comer stone of the third chapter in the processing (or the hardware) point-of-view and is enhanced in the fourth chapter to introduce the parallel learning-processing PLP notion. The Printed Circuit Board PCB technique is applied for the implementation of PLP-based neuron Bidirectional Associative Memory BAM using the cad tool of EEDIII that simulates it and shows the technique limited capabilities. The powerful Very Hardware Description Language VHDL is introduced and used to implement more suitable versions of the previous circuit and other, to be downloaded on a Field Programmable Gate Arrays FPGA chips. The PLP neuron-based BAM implementation is enhanced further by the introduction of the encodingcomparing technique as a user interface with the network as well as the expandability technique based on the suggested systolic-like architecture. Finally. the bus-based architecture technique is presented for the implementation of the Hopfield ANN. 1998 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/15239/1/Saffih_Faycal.pdf Saffih , Faycal (1998) Digital implementation of artificial neural networks / Saffih Faycal. Masters thesis, Universiti Malaya. http://studentsrepo.um.edu.my/15239/
spellingShingle Q Science (General)
QA75 Electronic computers. Computer science
Saffih , Faycal
Digital implementation of artificial neural networks / Saffih Faycal
title Digital implementation of artificial neural networks / Saffih Faycal
title_full Digital implementation of artificial neural networks / Saffih Faycal
title_fullStr Digital implementation of artificial neural networks / Saffih Faycal
title_full_unstemmed Digital implementation of artificial neural networks / Saffih Faycal
title_short Digital implementation of artificial neural networks / Saffih Faycal
title_sort digital implementation of artificial neural networks / saffih faycal
topic Q Science (General)
QA75 Electronic computers. Computer science
url http://studentsrepo.um.edu.my/15239/1/Saffih_Faycal.pdf
http://studentsrepo.um.edu.my/15239/
url_provider http://studentsrepo.um.edu.my/