VTU Online Courses

Fuzzy Sets, Logic and Systems & Applications

@VTU COE

0.0

(0) 2 Students

What you will learn

None

The course is designed to give a solid grounding of fundamental concepts of fuzzy logic and its applications. The level of the course is chosen to be such that all students aspiring to be a part of computational intelligence directly or indirectly in near future should get these concepts.

Lecture 1:Introduction: Fuzzy Sets, Logic and Systems & Applications

Preview 29:35

Lecture 2: Introduction - Real Life Applications of Fuzzy Systems

Preview 33:18

Lecture 3: Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB - I

Preview 29:49

Lecture 4: Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB - II

Preview 25:56

Lecture 5: Membership Functions

Preview 30:51

Lecture 6: Membership Functions-II

Preview 39:09

Lecture 7: Nomenclatures used in Fuzzy Set Theory-I

Preview 36:45

Lecture 8: Nomenclatures used in Fuzzy Set Theory-II

Preview 31:15

Lecture 9: Nomenclatures used in Fuzzy Set Theory-III

Preview 33:34

Lecture 10: Set Theoretic Operations on Fuzzy Sets-I

Preview 30:44

Lecture 11: Set Theoretic Operations on Fuzzy Sets-II

Preview 20:38

Lecture 12: Properties of Fuzzy Sets-I

Preview 28:10

Lecture 13: Properties of Fuzzy Sets-II

Preview 30:15

Lecture 14: Properties of Fuzzy Sets-III

Preview 26:22

Lecture 15: Properties of Fuzzy Sets-IV

Preview 34:16

Lecture 16: Properties of Fuzzy Sets-V

Preview 35:26

Lecture 17: Distance between Fuzzy Sets-I

Preview 33:39

Lecture 18: Distance between Fuzzy Sets-II

Preview 32:23

Lecture 19: Distance between Fuzzy Sets-III

Preview 38:19

Lecture 20: Arithmetic Operations on Fuzzy Numbers-I

Preview 28:28

Lecture 21: Arithmetic Operations on Fuzzy Numbers-II

Preview 33:37

Lecture 22: Arithmetic Operations on Fuzzy Numbers-III

Preview 35:48

Lecture 23: Complement of Fuzzy Sets

Preview 34:24

Lecture 24: T-norm Operators

Preview 29:23

Lecture 25: S-norm Operators

Preview 29:04

Lecture 26: Parameterized T-Norm Operators

Preview 28:14

Lecture 27: Parameterized S-Norm Operators

Preview 26:10

Lecture 28: Fuzzy Relation-I

Preview 38:51

Lecture 29: Fuzzy Relation-II

Preview 27:58

Lecture 30: Operations on Crisp and Fuzzy Relations

Preview 28:40

Lecture 31: Projection of Fuzzy Relation Set

Preview 27:32

Lecture 32: Cylindrical Extension of Fuzzy Set

Preview 31:02

Lecture 33: Properties of Fuzzy Relation-I

Preview 23:23

Lecture 34: Properties of Fuzzy Relation-II

Preview 32:23

Lecture 35: Extension Principle

Preview 43:12

Lecture 36: Composition of Fuzzy Relations

Preview 24:23

Lecture 37: Properties of Composition of Fuzzy Relations

Preview 36:45

Lecture 38: Fuzzy Tolerance and Equivalence Relations-I

Preview 25:37

Lecture 39: Fuzzy Tolerance and Equivalence Relations-II

Preview 24:46

Lecture 40: Fuzzy Tolerance and Equivalence Relations-III

Preview 19:41

Lecture 41: Linguistic Hedges

Preview 27:33

Lecture 42: Linguistic Hedges and Negation/ Complement and Connectives

Preview 26:13

Lecture 43: Concentration and Dilation & Composite Linguistic Term and Some Examples

Preview 26:15

Lecture 44: Dilation and Composite Linguistic Term and Some Examples

Preview 33:02

Lecture 45: Some Examples on Composite Linguistic Terms

Preview 22:28

Lecture 46: Contrast Intensification of Fuzzy Sets

Preview 29:13

Lecture 47: Orthogonality of Fuzzy Sets

Preview 28:39

Lecture 48: Fuzzy Rules and Fuzzy Reasoning-I

Preview 32:35

Lecture 49: Fuzzy Rules and Fuzzy Reasoning-II

Preview 25:26

Lecture 50: Fuzzy Inference System

Preview 53:59

Mamdani Fuzzy Model-I

Preview 27:53

Mamdani Fuzzy Model-II

Preview 32:04

Mamdani Fuzzy Model-III

Preview 36:03

Example on Mamdani Fuzzy Model for Single Antecedent with Three Rules

Preview 36:59

Example on Mamdani Fuzzy Model for Two Antecedents with Four Rules

Preview 22:02

Lecture 56: Larsen Fuzzy Model-I

Preview 32:42

Lecture 57: Larsen Fuzzy Model-II

Preview 29:04

Lecture 58: Larsen Fuzzy Model-III

Preview 52:01

Lecture 59: Tsukamoto Fuzzy Model

Preview 64:32

Lecture 60: TSK Fuzzy Model

Preview 76:12

No Discussion Found

0.0

0 Reviews

Meet Your Instructor

@VTU COE

Instructor

0.0 Rating

40 Students

718 Courses

About Instructor

VTU is one of the largest Technological Universities in India with 24 years of Tradition of excellence in Engineering & Technical Education, Research and Innovations. It came into existence in the year 1998 to cater the needs of Indian industries for trained technical manpower with practical experience and sound theoretical knowledge.

Free

Course Duration

32 h 24 m 40 s
Course Level

Intermediate
Student Enrolled

2
Language

English

This Course Includes

32 h 24 m 40 s Video Lectures
0 Quizzes
0 Assignments
0 Downloadable Resources
Full Lifetime Access
Certificate of Completion

What you will learn

Week 1 - Introduction: Fuzzy Sets, Logic and Systems & Applications

Week 2: Nomenclature Terms and Set Theoretic Operations used in Fuzzy Sets

Week 3: Set Theoretic Operations and Fuzzy Set Properties

Week 4: Fuzzy Set Properties and Distance between Fuzzy Sets

Week 5: Arithmetic Operations on Fuzzy Numbers, Complement, T-norm and S-norm for Fuzzy Sets

Week 6: Parmeterized T-Norms, Parameterized S-Norms, Fuzzy Relation and its Operations

Week 7: Projection, Cylindrical Extension and Properties of Fuzzy Relation

Week 8 - Composition of Fuzzy Relations and Its Properties, Fuzzy Tolerance and Equivalence Relations

Week 9 - Linguistic Hedges, Negation/ Complement, Connectives, Concentration, Dilation, and Some Examples on Composite Linguistic Terms

Week 10 - Contrast Intensification of Fuzzy Sets, Orthogonality of Fuzzy Sets, Fuzzy Rules, Fuzzy Reasoning, and Fuzzy Inference System

Week 11 - Fuzzy Inference System: Mamdani Fuzzy Model and Examples

Week 12 - Fuzzy Inference System: Larsen Fuzzy Model, Tsukamoto Fuzzy Model, and TSK Fuzzy Model

No Discussion Found

0.0

Meet Your Instructor

@VTU COE

About Instructor

Free

This Course Includes