Knowledge-Based Neurocomputing: A Fuzzy Logic Approach - Eyal Kolman,Michael Margaliot
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Toimitus 17-23 arkipäivässä
30 päivän palautusoikeus
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 ... Täydellinen kuvaus
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Kuvaus
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.
Lisätietoja
| Kirjoittaja | Eyal Kolman, Michael Margaliot |
|---|---|
| Julkaisija | Springer Berlin Heidelberg |
| Series | Studies in Fuzziness and Soft Computing |
| Julkaisuvuosi | 2009 |
| Kannen tyyppi | Kovakantinen |
| EAN | 9783540880769 |