Description
Book SynopsisFuzzy logic has virtually exploded over the landscape of emerging technologies, becoming an integral part of myriad applications and a standard tool for engineers. Until recently, most of the attention and applications have centered on fuzzy systems implemented in software. But these systems are limited. Problems that require real-time operation, low area, or low power consumption demand hardware designed to the fuzzy paradigm - and engineers with the background and skills to design it.
Microelectronic Design of Fuzzy Logic-Based Systems offers low-cost answers to issues that software cannot resolve. From the theoretical, architectural, and technological foundation to design tools and applications, it serves as your guide to effective hardware realizations of fuzzy logic.
Review fuzzy logic theory and the basic issues of fuzzy sets, operators, and inference mechanisms
Explore the trade-offs between efficient theoretical behavior and practical hardware realizations
Discover the properties of the possible microelectronic realizations of fuzzy systems - conventional processors, fuzzy coprocessors, and fuzzy chips
Investigate the design of fuzzy chips that implement the whole fuzzy inference method into silicon
Analyze analog, digital, and mixed-signal techniques
Reduce your design effort for fuzzy systems with CAD tools - learn the requirements they should meet and survey current environments.
Put it all together - see examples and case studies illustrating how all of this is used to solve particular problems related to control and neuro-fuzzy applicationsTable of Contents1. Introduction. 2. Fuzzy Set Theory, 3. Fuzzy Inference Systems, 4. Fuzzy System Development, 5. Fuzzy System Verification, 6. Hardware Realization of Fuzzy Systems, 7. Continuous-Time Analog Techniques for Designing Fuzzy Integrated Circuits, 8. Discrete-Time Analog Techniques for Designing Fuzzy Integrated Circuits, 9. Digital Techniques for Designing Fuzzy Integrated Circuits, 10. Fuzzy System Synthesis, 11. Fuzzy Systems as Controllers, 12. Fuzzy Systems as Approximators, Index
