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Springer Modular Neural Networks & Type-2 Fuzzy Systems - Pattern Recognition

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Description

This comprehensive academic text explores hybrid intelligent systems that combine type-2 fuzzy logic and modular neural networks for advanced pattern recognition applications. The book covers foundational theory alongside practical implementations, including detailed discussions of type-2 fuzzy models, optimization techniques for type-2 fuzzy systems, and modular neural network architectures. Designed for researchers and practitioners in artificial intelligence and machine learning, it demonstrates how hybrid systems integrate fuzzy logic, neural networks, and bio-inspired optimisation algorithms to solve complex pattern recognition problems. Published by Springer as part of the Studies in Computational Intelligence series, this volume offers both theoretical insights and practical guidance for developing intelligent systems capable of handling real-world pattern recognition challenges.

Key Features

Covers type-2 fuzzy logic theory and application methodologies for pattern recognition tasks.

Explores modular neural network architectures and their integration with fuzzy systems.

Includes optimisation techniques for both type-2 fuzzy systems and modular neural networks.

Demonstrates hybrid intelligent systems combining fuzzy logic, neural networks, and bio-inspired algorithms.

Part of Springer's Studies in Computational Intelligence series (volume 389).

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
30 November 2013
Listed Since
01 November 2013

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