Knowledge-Based Neurocomputing: A Fuzzy Logic Approach - Eyal Kolman,Michael Margaliot
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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 ... Pilns apraksts
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Aprašymas
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.
Vairāk informācijas
| Autors | Eyal Kolman, Michael Margaliot |
|---|---|
| Izdevējs | Springer Berlin Heidelberg |
| Series | Studies in Fuzziness and Soft Computing |
| Izlaides gads | 2009 |
| Vāka tips | Cietais vāks |
| EAN | 9783540880769 |