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Springer Knowledge-Based Neurocomputing: A Fuzzy Logic Approach

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Description

Explore the latest advancements in computational intelligence with Knowledge-Based Neurocomputing: A Fuzzy Logic Approach. Published by Springer as part of the Studies in Fuzziness and Soft Computing series, this monograph provides a deep look into the state-of-the-art methods within the field. The text introduces a novel fuzzy-rule base known as the Fuzzy All-permutations Rule-Base (FARB). It presents new connections between artificial neural networks and FARB, demonstrating how inferring the FARB using standard fuzzy logic theory tools yields an input-output map mathematically equivalent to an artificial neural network. This work is essential for researchers and professionals looking to understand the mathematical relationships between fuzzy logic systems and neural architectures.

Key Features

Introduces the novel Fuzzy All-permutations Rule-Base (FARB) for advanced computational modeling.

Establishes new connections between artificial neural networks and fuzzy-rule bases.

Provides mathematical proof showing the equivalence between FARB input-output maps and artificial neural networks.

Part of the recognized Studies in Fuzziness and Soft Computing series (Volume 234) from Springer.

Details the current state-of-the-art in the field of knowledge-based neurocomputing.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
21 October 2010
Listed Since
28 December 2010

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