Why enroll

Participants should join this course to understand how fuzzy logic handles uncertainty and real-world complexity better than traditional logic.It helps build a strong foundation for computational intelligence, AI, and intelligent control systems.The course is suitable for beginners who want practical and industry-relevant knowledge.

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Course content

The course is readily available, allowing learners to start and complete it at their own pace.

Fuzzy Sets, Logic and Systems & Applications

25 Lectures

752 min

Fuzzy Sets, Logic and Systems & Applications- Course Overview
Preview
3 min
Introduction: Fuzzy Sets, Logic and Systems & Applications
29 min
Introduction: Real Life Applications of Fuzzy Systems
32 min
Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB - I
29 min
Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB - II
25 min
Membership Functions
30 min
Membership Functions- ll
39 min
Nomenclatures Used In Fuzzy Set Theory
36 min
Nomenclatures Used In Fuzzy Set Theory -II
31 min
Nomenclatures Used In Fuzzy Set Theory-III
33 min
Set Theoretic Operation On Fuzzy Sets
30 min
Set Theoretic Operation on Fuzzy Sets- II
20 min
Properties of Fuzzy Sets - 1
28 min
Properties of Fuzzy Sets - 2
30 min
Properties of Fuzzy Sets - 3
26 min
Properties of Fuzzy Sets - 4
34 min
Properties of Fuzzy Sets
35 min
Distance between Fuzzy Sets
33 min
Distance between Fuzzy Sets - 2
32 min
Distance between Fuzzy Sets - 3
38 min
Arithmetic Operations on Fuzzy Numbers
28 min
Arithmetic Operations on Fuzzy Numbers-II
33 min
Arithmetic Operations on Fuzzy Numbers - 2
35 min
Compement of Fuzzy Sets
34 min
T-norm Operators
29 min

Course details

This course is designed to provide a strong foundation in the fundamental concepts of fuzzy logic and its practical applications. It introduces the motivation behind fuzzy logic and explains how it differs from classical Boolean logic. Students will learn about fuzzy sets, membership functions, and fuzzy relations in a simple and intuitive manner. The course covers fuzzy inference systems and the process of fuzzy decision-making. Learners will understand how uncertainty and imprecision are handled in real-world problems using fuzzy logic. The course also introduces common fuzzy reasoning techniques and rule-based systems. Practical examples are used to demonstrate applications of fuzzy logic in control systems, decision support, and intelligent systems. The content is structured to be accessible to students from diverse backgrounds. The course prepares learners for further studies in computational intelligence. By the end, students will have a clear understanding of how fuzzy logic is applied in modern engineering and technology domains.

Source: IIT Kanpur-NPTEL[Youtube Channel]

Course suitable for

Automotive
Electrical
Engineering & Design
Project Management
Research & Developmnet

Key topics covered

Fuzzy Sets, Logic and Systems & Applications – Course Overview
Introduction: Fuzzy Sets, Logic and Systems & Applications
Introduction: Real-Life Applications of Fuzzy Systems
Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB – I
Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB – II
Membership Functions
Membership Functions – II
Nomenclatures Used in Fuzzy Set Theory – I
Nomenclatures Used in Fuzzy Set Theory – II
Nomenclatures Used in Fuzzy Set Theory – III
Set Theoretic Operation on Fuzzy Sets – I
Set Theoretic Operation on Fuzzy Sets – II
Properties of Fuzzy Sets – I
Properties of Fuzzy Sets – II
Properties of Fuzzy Sets – III
Properties of Fuzzy Sets – IV
Properties of Fuzzy Sets (Summary)
Distance between Fuzzy Sets – I
Distance between Fuzzy Sets – II
Distance between Fuzzy Sets – III
Arithmetic Operations on Fuzzy Numbers – I
Arithmetic Operations on Fuzzy Numbers – II
Arithmetic Operations on Fuzzy Numbers – III
Complement of Fuzzy Sets
T-norm Operators

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