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.
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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.
Knowledge-Based Neurocomputing: A Fuzzy Logic Approach
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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Knowledge-Based Neurocomputing: A Fuzzy Logic Approach
100
Knowledge-Based Neurocomputing: A Fuzzy Logic Approach
100Paperback(Softcover reprint of hardcover 1st ed. 2009)
$109.99
109.99
In Stock
Product Details
| ISBN-13: | 9783642099854 |
|---|---|
| Publisher: | Springer Berlin Heidelberg |
| Publication date: | 12/15/2010 |
| Series: | Studies in Fuzziness and Soft Computing , #234 |
| Edition description: | Softcover reprint of hardcover 1st ed. 2009 |
| Pages: | 100 |
| Product dimensions: | 6.10(w) x 9.25(h) x 0.01(d) |
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