Graduate Thesis Or Dissertation
 

The architecture and design of a neural network classifier

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/nk322h502

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  • The objective of this thesis is to present the architecture and design of a neural network-based pattern classifier. The classifier detects textual characters which have been translated, rotated, and corrupted by noise. This form of pattern classifier differs significantly from traditional pattern classifiers. The neural network architecture used in implementing this classifier incorporates massive parallelism, distributed memory, fault tolerance, and is capable of learning. Traditional classifiers rarely incorporate all these features. The classifier's neural network topology, interconnect structure, learning algorithms, test methodology, and test results are presented in the thesis.
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  • File scanned at 300 ppi (Monochrome) using ScandAll PRO 1.8.1 on a Fi-6770A in PDF format. CVista PdfCompressor 5.0 was used for pdf compression and textual OCR.
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