Neuro-Fuzzy Architectures and Hybrid Learning

• Κύριος συγγραφέας: Rutkowska, Danuta (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2002.
• Έκδοση: 1st ed. 2002.
• Σειρά: Studies in Fuzziness and Soft Computing, 85
• Θέματα: Artificial intelligence.; Artificial Intelligence.

The main idea of this book is to present novel connectionist architectures of neuro-fuzzy systems, especially those based on the logical approach to fuzzy inference. In addition, hybrid learning methods are proposed to train the networks. The neuro-fuzzy architectures plus hybrid learning are consid...

Πίνακας περιεχομένων:

• 1 Introduction
• 2 Description of Fuzzy Inference Systems
• 2.1 Fuzzy Sets
• 2.2 Approximxate Reasoning
• 2.3 Fuzzy Systems
• 3 Neural Networks and Neuro-Fuzzy Systems
• 3.1 Neural Networks
• 3.2 Fuzzy Neural Networks
• 3.3 Fuzzy Inference Neural Networks
• 4 Neuro-Fuzzy Architectures Based on the Mamdani Approach
• 4.1 Basic Architectures
• 4.2 General Form of the Architectures
• 4.3 Systems with Inference Based on Bounded Product
• 4.4 Simplified Architectures
• 4.5 Architectures Based on Other Defuzzification Methods
• 4.6 Architectures of Systems with Non-Singleton Fuzzifier
• 5 Neuro-Fuzzy Architectures Based on the Logical Approach
• 5.1 Mathematical Descriptions of Implication-Based Systems
• 5.2 NOCFS Architectures
• 5.3 OCFS Architectures
• 5.4 Performance Analysis
• 5.5 Computer Simulations
• 6 Hybrid Learning Methods
• 6.1 Gradient Learning Algorithms
• 6.2 Genetic Algorithms
• 6.3 Clustering Algorithms
• 6.4 Hybrid Learning
• 6.5 Hybrid Learning Algorithms for Neuro-Fuzzy Systems
• 7 Intelligent Systems
• 7.1 Artificial and Computational Intelligence
• 7.2 Expert Systems
• 7.3 Intelligent Computational Systems
• 7.4 Perception-Based Intelligent Systems
• 8 Summary
• List of Figures
• List of Tables
• References.