Fuzzy Neural Intelligent Systems: Mathematical Foundation and the Applications in EngineeringCRC Press, 2018 M10 3 - 392 páginas Although fuzzy systems and neural networks are central to the field of soft computing, most research work has focused on the development of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems, especially their mathematical foundations. Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field. |
Contenido
| 1 | |
Determination of Membership Functions | 23 |
Mathematical Essence and Structures of Feedforward Artificial Neural Networks | 47 |
Functionallink Neural Networks and Visualization Means of Some Mathematical Methods | 72 |
Flat Neural Networks and Rapid Learning Algorithms | 90 |
Basic Structure of Fuzzy Neural Networks | 113 |
Mathematical Essence and Structures of Feedback Neural Networks and Weight Matrix Design | 126 |
Generalized Additive Weighted Multifactorial Function and its Applications to Fuzzy Inference and Neural Networks | 140 |
Adaptive Fuzzy Controllers Based on Variable Universes | 181 |
The Basics of Factor Spaces | 197 |
Neuron Models Based on Factor Spaces Theory and Factor Space Canes | 219 |
Foundation of NeuroFuzzy Systems and an Engineering Application | 241 |
Data Preprocessing | 255 |
Control of a Flexible Robot Arm using a Simplified Fuzzy Controller | 267 |
Application of NeuroFuzzy Systems Development of a Fuzzy Learning Decision Tree and Application to Tactile Recognition | 295 |
Fuzzy Assessment Systems of Rehabilitative Process for CVA Patients | 322 |
The Interpolation Mechanism of Fuzzy Control | 152 |
The Relationship between Fuzzy Controllers and PID Controllers | 165 |
A DSPbased Neural Controller for a Multidegree Prosthetic Hand | 351 |
Otras ediciones - Ver todas
Fuzzy Neural Intelligent Systems: Mathematical Foundation and the ... Hongxing Li,C.L. Philip Chen,Han-Pang Huang Vista previa limitada - 2018 |
Fuzzy Neural Intelligent Systems: Mathematical Foundation and the ... Hongxing Li,C.L. Philip Chen,Han-Pang Huang Vista previa limitada - 2018 |
Fuzzy Neural Intelligent Systems: Mathematical Foundation and the ... Hongxing Li,C.L. Philip Chen,Han-Pang Huang Sin vista previa disponible - 2000 |
Términos y frases comunes
A/P direction activation functions Adaptive Fuzzy Controllers ANFIS artificial neural networks chapter coefficients comparison computation control ability CVA patients decision tree defined defuzzification degree of membership denoted discussed EMG signal enhancement nodes Equation example Expression factor space factor space cane feedforward neural network flexible arm functional-link fuzzy inference fuzzy logic fuzzy model fuzzy neural network fuzzy sets fuzzy statistical Fuzzy Systems given hidden layer identity function IEEE Transactions input variables interpolation function kinetic state assessment learning algorithm linear linear programming M/L direction mapping means membership function method model of neurons monotonic multifactorial function neuro-fuzzy neurons nonlinear object on-line output parameters PID controller piecewise problem Proof pseudoinverse respect rule base satisfies shown in Figure simplified fuzzy control Step t-norm Table tactile sensing Theorem time-series training data update vector weight matrix Xi+1