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...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2009, 2009
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| Edition: | 1st ed. 2009 |
| Series: | Studies in Fuzziness and Soft Computing
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | 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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| Physical Description: | XVI, 100 p online resource |
| ISBN: | 9783540880776 |