James K. Peckol

Introduction to Fuzzy Logic

• Gebundenes Buch

Produktbeschreibung

Learn more about the history, foundations, and applications of fuzzy logic in this comprehensive resource by an academic leader

Introduction to Fuzzy Logic delivers a high-level but accessible introduction to the rapidly growing and evolving field of fuzzy logic and its applications. Distinguished engineer, academic, and author James K. Peckol covers a wide variety of practical topics, including the differences between crisp and fuzzy logic, the people and professions who find fuzzy logic useful, and the advantages of using fuzzy logic.

While the book assumes a solid foundation in embedded systems, including basic logic design, and C/C++ programming, it is written in a practical and easy-to-read style that engages the reader and assists in learning and retention. The author includes introductions of threshold and perceptron logic to further enhance the applicability of the material contained within.

After introducing readers to the topic with a brief description of the history and development of the field, Introduction to Fuzzy Logic goes on to discuss a wide variety of foundational and advanced topics, like:
_ A review of Boolean algebra, including logic minimization with algebraic means and Karnaugh maps
_ A discussion of crisp sets, including classic set membership, set theory and operations, and basic classical crisp set properties
_ A discussion of fuzzy sets, including the foundations of fuzzy sets logic, set membership functions, and fuzzy set properties
_ An analysis of fuzzy inference and approximate reasoning, along with the concepts of containment and entailment and relations between fuzzy subsets

Perfect for mid-level and upper-level undergraduate and graduate students in electrical, mechanical, and computer engineering courses, Introduction to Fuzzy Logic covers topics included in many artificial intelligence, computational intelligence, and soft computing courses. Math students and professionals ina wide variety of fields will also significantly benefit from the material covered in this book.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Wiley / Wiley & Sons
• Artikelnr. des Verlages: 1W119772610
• 1. Auflage
• Seitenzahl: 304
• Erscheinungstermin: 2. August 2021
• Englisch
• Abmessung: 250mm x 175mm x 21mm
• Gewicht: 670g
• ISBN-13: 9781119772613
• ISBN-10: 1119772613
• Artikelnr.: 59984493

Autorenporträt

James K. Peckol, PhD, is Principal Lecturer Emeritus in the Department of Electrical and Computer Engineering at the University of Washington in Seattle. He has over 50 years of experience in engineering and education in the fields of software, digital, medical, and embedded systems design and development.

Inhaltsangabe

Preface (1-11)

Acknowledgements ( 1 )

About the Author ( 1 )

Introduction

Chapter 1 A Brief Introduction and History 1

Introduction 1

Models of Human Reasoning 1

The Early Foundation 2

Building On The Past - From Those Who Laid The Foundation 3

A Learning and Reasoning Taxonomy 4

Rote Learning 4

Learning With a Teacher 5

Learning by Example 5

Analogical or Metaphorical Learning 6

Learning by Problem Solving 6

Learning By Discovery 7

Crisp and Fuzzy Logic 7

Starting To Think Fuzzy 7

History Revisited - Early Mathematics 9

Foundations of Fuzzy Logic 9

Fuzzy Logic And Approximate Reasoning 9

Non-Monotonic Reasoning 11

Sets and Logic 12

Classical Sets 12

Fuzzy Subsets 13

Fuzzy Membership Functions 14

Expert Systems 16

Summary 17

Review questions 17

Chapter 2 A Review of Boolean Algebra 19

Introduction to crisp logic and Boolean Algebra 19

Introduction to algebra 20

Postulates 20

Theorems 23

Getting some practice 24

Getting to work 24

Boolean Algebra 24

Implementation 28

Logic minimization 29

Algebraic Means 29

Karnaugh Maps 30

Applying the K-map 30

2 Variable K-Maps 31

3 Variable K-Maps 32

4 Variable K-Maps 33

Going Backwards 33

Don't Care Variables 35

Summary 37

Review questions 37

Chapter 3 Crisp Sets and Sets and More Sets 38

Introducing the Basics 38

Introduction to Classic Sets and Set Membership 41

Classic Sets 41

Set Membership 41

Basic Classic Crisp Set Properties 45

Exploring Sets and Set Membership 46

Fundamental Terminology 47

Elementary Vocabulary 47

Classical Set Theory and Operations 49

Classic Set Logic 49

Basic Classical Crisp Set Properties 50

Basic Crisp Applications - A First Step 57

Summary 59

Review questions 60

Chapter 4 Fuzzy Sets and Sets and More Sets 61

Introducing Fuzzy 61

Early Mathematics 62

Foundations of Fuzzy Sets Logic 62

Introducing the Basics 64

Introduction to Fuzzy Sets and Set Membership 66

Fuzzy Subsets and Fuzzy Logic 66

Fuzzy Membership Functions 68

Fuzzy Set Theory and Operations 71

Fundamental Terminology 71

Basic Fuzzy Set Properties and Operations 72

Basic Fuzzy Applications - A First Step 83

A Crisp Activity revisited 83

Fuzzy Imprecision and Membership Functions 86

Linear Membership Functions 87

Curved Membership Functions 90

Summary 95

Review questions 96

Chapter 5 What do You Mean by That? 97

Language, Linguistic Variables, Sets And Hedges 97

Symbols And Sounds To Real World Objects 99

Crisp Sets a Second Look 99

Fuzzy Sets a Second Look 103

Linguistic Variables 103

Membership Functions 105

Hedges 106

Summary 110

Review questions 111

Chapter 6 If There Were Four Philosophers 112

Fuzzy Inference And Approximate Reasoning 112

Equality 113

Containment And Entailment 116

Relations Between Fuzzy Subsets 119

Union and Intersection 119