Fuzzy Hardware, 1998 Architectures and Applications

Fuzzy hardware developments have been a major force driving the applications of fuzzy set theory and fuzzy logic in both science and engineering. This volume provides the reader with a comprehensive up-to-date look at recent works describing new innovative developments of fuzzy hardware.
An important research trend is the design of improved fuzzy hardware. There is an increasing interest in both analog and digital implementations of fuzzy controllers in particular and fuzzy systems in general. Specialized analog and digital VLSI implementations of fuzzy systems, in the form of dedicated architectures, aim at the highest implementation efficiency. This particular efficiency is asserted in terms of processing speed and silicon utilization. Processing speed in particular has caught the attention of developers of fuzzy hardware and researchers in the field.
The volume includes detailed material on a variety of fuzzy hardware related topics such as:

• Historical review of fuzzy hardware research
• Fuzzy hardware based on encoded trapezoids
• Pulse stream techniques for fuzzy hardware
• Hardware realization of fuzzy neural networks
• Design of analog neuro-fuzzy systems in CMOS digital technologies
• Fuzzy controller synthesis method
• Automatic design of digital and analog neuro-fuzzy controllers
• Electronic implementation of complex controllers
• Silicon compilation of fuzzy hardware systems
• Digital fuzzy hardware processing
• Parallel processor architecture for real-time fuzzy applications
• Fuzzy cellular systems

Fuzzy Hardware: Architectures and Applications is a technical reference book for researchers, engineers and scientists interested in fuzzy systems in general and in building fuzzy systems in particular.

Preface. 1. Fuzzy Hardware Research from Historical Point of View; M. Russo. 2. Three Generations of Fuzzy Hardware; L. Peters, Shuwei Gou. 3. Hardware Realization of Fuzzy Neural Networks; C.H. Poskar, et al. 4. AFAN - a Tool for the Automatic Design of Digital and Analog Neuro-Fuzzy Controllers; R. Gonzalez Carvajal, et al. 5. Silicon Compilation of Fuzzy Hardware Systems Based on Generic LR Fuzzy Cells; Yau-Hwang Kuo, Chao-Lieh Chen. 6. Serial Architectures for Efficient Digital Fuzzy Hardware Processing; L. de Salvador Carrasco, J. Gutierrez-Rios. 7. Automatic Implementation of Piecewise-Linear Fuzzy Systems Addressing Memory-Performance Trade-Off; R. Rovatti, et al. 8. A Parallel Processor Architecture for Real-Time Fuzzy Applications; G. Ascia, V. Catania. 9. Short Time Decision VLSI Fuzzy Processor; A. Gabrielli, et al. 10. Designing a Simple System to Greatly Accelerate the Learning Speed of a Large Class of Fuzzy Learning Methods; M. Russo. 11. Fuzzy Controller Synthesis Method; J.-P. Deschamps. 12. Fuzzy Hardware Based on Encoded Trapezoids; A. Ruiz, et al. 13. Pulse Stream Techniques for Fuzzy Hardware; F. Colodro Ruiz, et al. 14. Fuzzy Cellular System: Characteristics and Architecture; R. Caponetto, et al. 15. Fuzzy Wavelets for Feature Extraction and Failure Classification; G. Vachtsevanos, et al. 16. A Building Block Approach to the Design of Analog Neuro-Fuzzy Systems in CMOS Digital Technologies; F. Vidal-Verdu, et al. 17. Electronic Implementationof Complex Controllers; A. Sanz, J. Falco. Contributors. Index.

Fuzzy hardware developments have been a major force driving the applications of fuzzy set theory and fuzzy logic in both science and engineering. This volume provides the reader with a comprehensive up-to-date look at recent works describing new innovative developments of fuzzy hardware. There is an increasing interest in both analog and digital implementations of fuzzy controllers in particular and fuzzy systems in general. Specialized analog and digital VLSI implementations of fuzzy systems, in the form of dedicated architectures, aim at the highest implementation efficiency. This particular efficiency is asserted in terms of processing speed and silicon utilization. Processing speed in particular has caught the attention of developers of fuzzy hardware and researchers in the field.