Knowledge-based Neurocomputing: A Fuzzy Logic Approach
Kolman, Eyal/ Margaliot, Michael
Sold by Revaluation Books, Exeter, United Kingdom
AbeBooks Seller since January 6, 2003
New - Hardcover
Condition: New
Quantity: 2 available
Add to basketSold by Revaluation Books, Exeter, United Kingdom
AbeBooks Seller since January 6, 2003
Condition: New
Quantity: 2 available
Add to basket1st edition. 100 pages. 9.50x6.50x0.25 inches. In Stock.
Seller Inventory # x-3540880763
In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB.
The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.
In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB.
The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.
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