Microelectronic Design of Fuzzy Logic-Based Systems

✍ Scribed by Iluminada Baturone (Author); Angel Barriga (Author); Carlos Jimenez-Fernandez (Author); Diego R. Lopez (Author); Santiago Sanchez-Solano (Author)

• Publisher: CRC Press
• Year: 2000
• Leaves: 338
• Edition: 1
• Category: Library

✦ Synopsis

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

✦ Table of Contents

INTRODUCTION

Methods for Information Representation and Processing

Fuzzy Sets and Fuzzy Logic

A Brief History of Fuzzy Logic

Fuzzy Logic Application Domain

FUZZY SET THEORY

Fuzzy Sets

The Concept of Membership Function

Terminology for Fuzzy Sets

Operations with Fuzzy Sets

Fuzzy Relations

FUZZY INFERENCE SYSTEMS

Linguistic Variables

Fuzzy Rules

Approximate Reasoning Techniques

Rule-Based Inference Mechanisms

Defuzzification Methods

Types of Fuzzy Systems

Structure of a Fuzzy System

FUZZY SYSTEM DEVELOPMENT

Definition of a Fuzzy System

CAD Tools for Fuzzy Systems

The Xfuzzy Development Environment

FUZZY SYSTEM VERIFICATION

Learning Techniques for Fuzzy Systems

Learning on XFL-Based Systems

Simulation of Fuzzy Systems

Simulation of XFL-Based Systems

On-Line Verification of XFL-Based Systems

HARDWARE REALIZATION OF FUZZY SYSTEMS

Fuzzy System Implementations Depending on the Application

Fuzzy System Realizations with General-Purpose Processors

Fuzzy System Realizations with Dedicated Hardware

CONTINUOUS-TIME ANALOG TECHNIQUES FOR DESIGNING FUZZY INTEGRATED CIRCUITS

The First Analog Fuzzy Integrated Circuits

Fully Parallel Architectures

Fuzzification Stage

Rule Processing Stage

Output Stage

Design of a Current-Mode CMOS Prototype

DISCRETE-TIME ANALOG TECHNIQUES FOR DESIGNING FUZZY INTEGRATED CIRCUITS

Sequential Architectures

Fuzzification Stage

Rule Processing Stage

Output Stage

Timing and Inference Speed of Discrete-Time Singleton Fuzzy ICs

Design of an SC CMOS Prototype

DIGITAL TECHNIQUES FOR DESIGNING FUZZY INTEGRATED CIRCUITS

The First Digital Fuzzy Integrated Circuits

Architectures of Digital Fuzzy IntegratedCircuits

Fuzzification Stage

Rule Processing and Defuzzification Stages

Active Rule-Driven Architecture with Simplified Defuzzification Methods

FUZZY SYSTEM SYNTHESIS

Hardware Synthesis of Fuzzy Systems

Describing Fuzzy Systems with a Hardware Description Language: VHDL

Tools for Hardware Synthesis in Xfuzzy

A Design Methodology for Fuzzy Systems

FUZZY SYSTEMS AS CONTROLLERS

Conventional Control Systems

Fuzzy Control Systems

Application Example: Ball Suspended by an Air Flow

FUZZY SYSTEMS AS APPROXIMATORS

Approximation Capability of Fuzzy Systems

Applications using Off-Chip Learning

Application using On-Chip Learning

✦ Subjects

Engineering & Technology;Electrical & Electronic Engineering;Circuits & Devices;Electrical Engineering Communications;Microelectronics;Electronics;Microelectronics