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E-raamat: Microelectronic Design of Fuzzy Logic-Based Systems

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(IMSE-CNM, Sevilla, Spain), (IMSE-CNM, Sevilla, Spain), (IMSE-CNM, Sevilla, Spain), (IMSE-CNM, Sevilla, Spain), (CICA Edificio CICA, Sevilla, Spain)
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This guide focuses on the means of mapping fuzzy concepts into working silicon. It explains the methodologies, procedures, circuit techniques, and CAD tools necessary for low-cost solutions compatible with existing digital and analog processing technologies. The book aims to provide a comprehensive discussion of the theoretical and practical issues concerning the hardware design of fuzzy systems, with special emphasis on microelectronic realizations. It serves both as a self-contained reference for scientists and engineers involved with knowledge-based computational techniques, and as a text for advanced courses on subjects such as non-conventional processors, advanced integrated circuit design, VLSI microsystems design, and fuzzy software design. The authors are affiliated with the University of Sevilla. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Fuzzy 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 applications
    • Introduction
    		1(6)
    Methods for Information Representation and Processing
    		1(1)
    Fuzzy Sets and Fuzzy Logic
    		2(1)
    A Brief History of Fuzzy Logic
    		3(1)
    Fuzzy Logic Application Domain
    		4(2)
    References
    		6(1)
    Fuzzy Set Theory
    		7(12)
    Fuzzy Sets
    		7(4)
    The Concept of Membership Function
    		8(2)
    Terminology for Fuzzy Sets
    		10(1)
    Operations with Fuzzy Sets
    		11(4)
    Union, Intersection, and Complement
    		11(1)
    Fuzzy Intersection: t-Norms
    		12(1)
    Fuzzy Union: s-Norms
    		13(1)
    Fuzzy Complement: c-Norms
    		14(1)
    Properties of Fuzzy Sets
    		15(1)
    Fuzzy Relations
    		15(3)
    Composition of Fuzzy Relations
    		16(2)
    References
    		18(1)
    Fuzzy Inference Systems
    		19(24)
    Linguistic Variables
    		19(1)
    Fuzzy Rules
    		20(5)
    Linguistic Connectives
    		20(1)
    Implication Function
    		21(4)
    Approximate Reasoning Techniques
    		25(4)
    Generalized Modus Ponens/Tollens
    		25(1)
    Compositional Rule of Inference
    		26(1)
    Aggregation Operator
    		27(2)
    Rule-Based Inference Mechanisms
    		29(2)
    Min-Max Inference
    		30(1)
    Product-Sum Inference
    		30(1)
    Defuzzification Methods
    		31(8)
    Conventional Defuzzification Methods
    		32(2)
    Simplified Defuzzification Methods
    		34(5)
    Types of Fuzzy Systems
    		39(1)
    Structure of a Fuzzy System
    		40(2)
    References
    		42(1)
    Fuzzy System Development
    		43(30)
    Definition of a Fuzzy System
    		43(5)
    Selection of System Variables
    		43(2)
    Rule Base Definition
    		45(3)
    Selection of Fuzzy Operators
    		48(1)
    CAD Tools for Fuzzy Systems
    		48(7)
    Specification Language
    		49(2)
    Facilities for System Definition
    		51(1)
    Fuzzy Operators
    		51(1)
    Integration with Other Tools
    		52(1)
    Facilities for Tuning, Verification, and Analysis
    		53(1)
    Synthesis Capabilities
    		53(2)
    The Xfuzzy Development Environment
    		55(16)
    The XFL Language
    		57(1)
    Structure of an XFL Definition
    		57(8)
    Describing Fuzzy Systems with Xfuzzy
    		65(6)
    Software Synthesis of XFL-Based Systems
    		71(1)
    References
    		71(2)
    Fuzzy System Verification
    		73(28)
    Learning Techniques for Fuzzy Systems
    		74(11)
    The Error Function
    		75(2)
    Gradient Descent Algorithms
    		77(5)
    Other Supervised Learning Algorithms
    		82(3)
    Learning on XFL-Based Systems
    		85(6)
    Command Line Interface
    		88(1)
    Graphical User Interface
    		88(3)
    Simulation of Fuzzy Systems
    		91(1)
    Simulation of XFL-Based Systems
    		92(4)
    Command Line Interface
    		94(1)
    Graphical User Interface
    		95(1)
    On-Line Verification of XFL-Based Systems
    		96(4)
    References
    		100(1)
    Hardware Realization of Fuzzy Systems
    		101(24)
    Fuzzy System Implementations Depending on the Application
    		101(4)
    Fuzzy System Realizations with General-Purpose Processors
    		105(4)
    Parallelism of Fuzzy Systems
    		105(1)
    Non-Standard Operations of Fuzzy Systems
    		105(1)
    Hardware Expansion of General-Purpose Processors
    		106(3)
    Fuzzy System Realizations with Dedicated Hardware
    		109(12)
    Hardware Realization Strategies
    		109(3)
    Implementation Techniques of Integrated Circuits
    		112(3)
    Design Methodologies of Integrated Circuits
    		115(1)
    Analog and Digital Design Styles
    		116(5)
    References
    		121(4)
    Continuous-Time Analog Techniques for Designing Fuzzy Integrated Circuits
    		125(56)
    The First Analog Fuzzy Integrated Circuits
    		125(2)
    Fully Parallel Architectures
    		127(9)
    Rule by Rule Architecture
    		128(2)
    Architecture That Shares Circuitry
    		130(2)
    Active Rule-Driven Architecture
    		132(4)
    Fuzzification Stage
    		136(9)
    Transconductance-Mode MFCs
    		137(3)
    Current-Mode MFCs
    		140(5)
    Rule Processing Stage
    		145(13)
    Minimum and Maximum Operators
    		146(5)
    Product Operators
    		151(6)
    Scaling Operators
    		157(1)
    Addition Operators
    		158(1)
    Output Stage
    		158(9)
    Fuzzy Representation of Consequents
    		160(1)
    Parametric Representation of Consequents
    		161(6)
    Design of a Current-Mode CMOS Prototype
    		167(9)
    References
    		176(5)
    Discrete-Time Analog Techniques for Designing Fuzzy Integrated Circuits
    		181(28)
    Sequential Architectures
    		182(3)
    Sequential Architecture for Mamdani-Type Fuzzy Systems
    		182(2)
    Sequential Architecture for Singleton Fuzzy Systems
    		184(1)
    Fuzzification Stage
    		185(4)
    Serial MFC
    		186(1)
    Parallel MFC
    		187(2)
    Rule Processing Stage
    		189(6)
    Minimum and Maximum Operators
    		189(3)
    Addition and Scaling Operators
    		192(2)
    Memory Cells
    		194(1)
    Output Stage
    		195(7)
    Fuzzy Representation of Consequents: Accumulator Circuits
    		195(1)
    Parametric Representation of Consequents: Discrete-Time Multiplier/Divider Circuits
    		196(6)
    Timing and Inference Speed of Discrete-Time Singleton Fuzzy ICs
    		202(1)
    Design of an SC CMOS Prototype
    		203(4)
    References
    		207(2)
    Digital Techniques for Designing Fuzzy Integrated Circuits
    		209(30)
    The First Digital Fuzzy Integrated Circuits
    		209(2)
    Architectures of Digital Fuzzy Integrated Circuits
    		211(5)
    Parallel Rule Processing Architectures
    		211(2)
    Sequential Rule Processing Architectures
    		213(1)
    Active Rule-Driven Architectures
    		214(2)
    Fuzzification Stage
    		216(4)
    Memory-Based Approach
    		216(1)
    Algorithm-Based Approach
    		217(3)
    Rule Processing and Defuzzification Stages
    		220(3)
    Active Rule-Driven Architecture with Simplified Defuzzification Methods
    		223(13)
    Implementation Options
    		224(2)
    Operation Modes and Timing Schemes
    		226(1)
    Performance Analysis
    		227(5)
    Prototypes
    		232(4)
    References
    		236(3)
    Fuzzy System Synthesis
    		239(24)
    Hardware Synthesis of Fuzzy Systems
    		239(2)
    Describing Fuzzy Systems with a Hardware Description Language: VHDL
    		241(4)
    Modeling Fuzzy Systems with VHDL
    		243(1)
    Fuzzy System Synthesis from VHDL
    		244(1)
    Tools for Hardware Synthesis in Xfuzzy
    		245(14)
    Synthesis Based on Off-Line Strategies
    		245(3)
    Using xftl
    		248(1)
    Synthesis Based on On-Line Strategies
    		249(3)
    VHDL Component Library
    		252(2)
    xfvhdl Output Files
    		254(2)
    Using xfvhdl
    		256(2)
    Limitations to the XFL Model
    		258(1)
    A Design Methodology for Fuzzy Systems
    		259(3)
    References
    		262(1)
    Fuzzy Systems as Controllers
    		263(22)
    Conventional Control Systems
    		264(3)
    Fuzzy Control Systems
    		267(6)
    Components of a Fuzzy Control System
    		269(2)
    Fuzzy Controller Development
    		271(2)
    Application Example: Ball Suspended by an Airflow
    		273(10)
    Controller Definition
    		273(3)
    System Simulation
    		276(2)
    On-Line Verification of the Controller
    		278(3)
    Hardware Design and Implementation of the Controller
    		281(2)
    References
    		283(2)
    Fuzzy Systems as Approximators
    		285(26)
    Approximation Capability of Fuzzy Systems
    		286(7)
    Local Piecewise Interpolation
    		286(1)
    Analysis of Singleton Fuzzy Systems
    		287(6)
    Applications Using Off-Chip Learning
    		293(7)
    Modeling of Non-Linear Static Systems
    		293(2)
    Analysis and Discussion of FPGA Implementations
    		295(5)
    Applications Using On-Chip Learning
    		300(9)
    Analysis and Discussion of ASIC Implementations
    		300(3)
    Identification of a Dynamic Plant
    		303(1)
    Prediction of Time Series
    		304(2)
    Adaptive Noise Cancellation System
    		306(3)
    References
    		309(2)
    Index 311


    Iluminada Baturone, Angel Barriga, Carlos Jimenez-Fernandez, Diego R. Lopez, Santiago Sanchez-Solano
    Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
    Püsilink: https://www.kriso.ee/db/97813519906916e.html
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