Knowledge-Based Neurocomputing: A Fuzzy Logic Approach
Michael Margaliot, Eyal Kolman
Sold by Buchpark, Trebbin, Germany
AbeBooks Seller since 30 September 2021
Used - Hardcover
Condition: Used - Fine
Quantity: 1 available
Add to basketSold by Buchpark, Trebbin, Germany
AbeBooks Seller since 30 September 2021
Condition: Used - Fine
Quantity: 1 available
Add to basketZustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
Seller Inventory # 4741333/12
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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