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Title: Fault Tolerance of Sigmoidal Feedforward Artificial Neural Networks
Researcher: Amit Prakash Singh
Guide(s): C.S. Rai and Pravin Chandra
University: Guru Gobind Singh Indraprastha University
Completed Date: 2011
Abstract: Artificial neural networks (ANN) are known for their parallel structure. Based on the analogy with the biological neural structure, the robustness of the ANN working under faulty conditions has been claimed. That is, it has been claimed that ANNs working under fault conditions degrades gracefully. With the advent of ANN implementations in hardware it has become imperative to study the fault (tolerant) characteristics of ANNs. The following properties may be inferred for ANNs (based on the analogy to the biological neural systems): newline The computation is massively distributed and parallel. newline Integration and storage of experience, which could be previous classification or association of learning data or, self - organization of experience. newline Consideration of new experience in the context of stored experience or, a newlinecontext - addressable structure. newline Ability to make accurate predictions about new situations on the basis of previously (self-) organized experiences or, generalization capability. newline A fault - tolerant architecture, in the sense that loss of a few neurons may be recoverable by adaptation of those remaining (perhaps with additional training) and/or by growth of new neurons or associations between neurons. newline...
Appears in Departments:University School of Information and Communication Technology

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02 abstract.pdf1.7 MBAdobe PDFView/Open
03 contents.pdf1.63 MBAdobe PDFView/Open
04 list of figure.pdf2.38 MBAdobe PDFView/Open
05 list of tables.pdf5.31 MBAdobe PDFView/Open
06 list of publication.pdf787.36 kBAdobe PDFView/Open
07 abbreviations.pdf699.99 kBAdobe PDFView/Open
08 chapter-1.pdf6.96 MBAdobe PDFView/Open
09 chapter-1.1.pdf9.12 MBAdobe PDFView/Open
10 chapter-2.pdf12.14 MBAdobe PDFView/Open
11 chapter-3.pdf5.63 MBAdobe PDFView/Open
12 chapter-4.pdf12.01 MBAdobe PDFView/Open
13 chapter-5.pdf18.1 MBAdobe PDFView/Open
14 chapter-6.pdf12.51 MBAdobe PDFView/Open
15 chapter-7.pdf1.86 MBAdobe PDFView/Open
16 chapter-7.1.pdf4.49 MBAdobe PDFView/Open
17 chapter-8.pdf933.69 kBAdobe PDFView/Open
18 chapter-8.1.pdf1.07 MBAdobe PDFView/Open
19 bibliography.pdf11.15 MBAdobe PDFView/Open

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