DocumentCode
2264444
Title
Pattern theory paradigm for system design
Author
Ross, Timothy D. ; Axtell, Mark L. ; Noviskey, Michael J. ; Gadd, David A.
Author_Institution
Wright Lab. & Veda Inc., USA
fYear
1993
fDate
16-18 Aug 1993
Firstpage
721
Abstract
A recent convergence of ideas from logic minimization, computational complexity, and machine learning theory has resulted in a promising new approach to robust pattern finding, called Pattern Theory. This paper demonstrates the robustness of this approach using experimental and theoretical considerations. The results of experiments in two applications, machine learning and image processing, are summarized
Keywords
computational complexity; image processing; learning (artificial intelligence); minimisation; decomposed function cardinality; image processing; machine learning; pattern theory paradigm; robust pattern finding; system design; Circuit testing; Combinational circuits; Computational complexity; Convergence; Digital-to-frequency converters; Image processing; Machine learning; Minimization; Programmable logic arrays; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
Conference_Location
Detroit, MI
Print_ISBN
0-7803-1760-2
Type
conf
DOI
10.1109/MWSCAS.1993.343180
Filename
343180
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