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Title: VLSI realization of artificial neural Networks using digital and mixed Signal hardware
Researcher: Nirmala Devi, M
Guide(s): Arumugam, S
Keywords: Artificial Neural Networks
Biological Neural Network
Central Nervous System
Very Large Scale Integration
Upload Date: 20-Oct-2014
University: Anna University
Completed Date: 01-02-2009
Abstract: A Biological Neural Network BNN forms the Central Nervous newlineSystem which has highly interconnected neurons to co ordinate all the newlinefunctions like reading and thinking Artificial Neurons are simple newlineabstractions of biological neurons programmed in software or modeled in newlinehardware Networks of artificial neurons known as Artificial Neural Networks newline ANN have a fraction of power of biological neural structures and they can newlinebe trained to solve many complex problems An ANN has the ability to learn newlineand it had been realized in software But learning is a recursive process newlineinvolving multiple iterations which takes a long time when implemented in newlinesoftware However availability of powerful resources at affordable cost has newlineopened up the interesting possibility of realizing ANN in hardware The focus newlineof the present work is on Very Large Scale Integration VLSI hardware newlinerealization of ANN so as to achieve flexibility portability and adaptability newline newline
Pagination: xxi, 187p.
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificate.pdf14.94 kBAdobe PDFView/Open
03_abstract.pdf21.76 kBAdobe PDFView/Open
04_acknowledgement.pdf16.38 kBAdobe PDFView/Open
05_content.pdf55.05 kBAdobe PDFView/Open
06_chapter1.pdf116.18 kBAdobe PDFView/Open
07_chapter2.pdf141.1 kBAdobe PDFView/Open
08_chapter3.pdf288.57 kBAdobe PDFView/Open
09_chapter4.pdf650.8 kBAdobe PDFView/Open
10_chapter5.pdf252.1 kBAdobe PDFView/Open
11_chapter6.pdf331.38 kBAdobe PDFView/Open
12_reference.pdf59.73 kBAdobe PDFView/Open
13_publication.pdf15.81 kBAdobe PDFView/Open
14_vitae.pdf6.23 kBAdobe PDFView/Open

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