Fuzzy Sets Logic and Systems & Applications

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About Course

Fuzzy Sets Logic and Systems & Applications

This course is intended for hackers, hobbyists, and professionals alike; Anyone that wants to get up-and-running quickly with a Fuzzy inference engine. If you have little or no knowledge of Fuzzy Logic, then this course is definitely for you!

At most, you will require basic math skills and access to Google Sheets along with a willingness to use Fuzzy Logic to solve a problem.

I will walk you through the complete design process of a Fuzzy Controller or Inference system – From fuzzification to inference methods up to and including defuzzification.

This course will have you implementing your first Fuzzy System to solve your real-world problem.

This course is succinct yet comprehensive – It covers each aspect in enough detail to serve as a foundation but not so deep that you get bogged down in the details; it teaches you the lion’s share…

 

Who this course is for:

  1. Hackers, hobbyists, and professionals with little or no knowledge of Fuzzy Logic.
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What Will You Learn?

  • Design and implement a Fuzzy Logic inference system.
  • Select appropriate Fuzzy Inference System Type (Takagi-Sugeno VS Mamdani).
  • Create a fuzzy rule base from heuristics / expert knowledge.
  • Select fuzzification, inference, and defuzzification methods.
  • Fault-find / analyze final Fuzzy system.
  • Identify opportunities for application performance enhancement using Fuzzy Logic.

Course Content

Fuzzy Sets, Logic and Systems & Applications

  • Lecture 60: TSK Fuzzy Model
    00:00
  • Lecture 44 – Dilation and Composite Linguistic Term and Some Examples
    00:00
  • Lecture 43 – Concentration, Dilation, Composite Linguistic Term
    00:00
  • Lecture 42 – Linguistic Hedges and Negation/Complement and Connectives
    00:00
  • Lecture 41 – Linguistic Hedges
    00:00
  • Lecture 40 – Fuzzy Tolerance and Equivalence Relations- III
    00:00
  • Lecture 39 – Fuzzy Tolerance and Equivalence Relations- II
    00:00
  • Lecture 38 – Fuzzy Tolerance and Equivalence Relations- I
    00:00
  • Lecture 37 – Properties of Composition of Fuzzy Relations
    00:00
  • Lecture 36 – Composition of Fuzzy Relations
    00:00
  • Lecture 35 – Extension Principle
    00:00
  • Lecture 34 – Properties of Fuzzy Relation 2
    00:00
  • Lecture 33 – Properties of Fuzzy Relation
    00:00
  • Lecture 32 – Cylindrical Extension of Fuzzy Set
    00:00
  • Lecture 45 – Some Examples on Composite Linguistic Terms
    00:00
  • Lecture 46 – Contrast Intensification of Fuzzy Sets
    00:00
  • Lecture 59: Tsukamoto Fuzzy Model
    00:00
  • Lecture 58: Larsen Fuzzy Model-III
    52:01
  • Lecture 57: Larsen Fuzzy Model-II
    00:00
  • Lecture 56: Larsen Fuzzy Model-I
    00:00
  • Lecture 55 – Example on Mamdani Fuzzy Model-II
    00:00
  • Lecture 54 – Example on Mamdani Fuzzy Model-I
    00:00
  • Lecture 53 – Mamdani Fuzzy Model (Part III)
    00:00
  • Lecture 52 – Mamdani Fuzzy Model (Part II)
    00:00
  • Lecture 51 – Mamdani Fuzzy Model (Part I)
    00:00
  • Lecture 50 – Fuzzy Inference System
    00:00
  • Lecture 49 – Fuzzy Rules and Fuzzy Reasoning
    00:00
  • Lecture 48 – Fuzzy Rules and Fuzzy Reasoning
    00:00
  • Lecture 47 – Orthogonality of Fuzzy Sets
    00:00
  • Lecture 31 – Projection of Fuzzy Relation Set
    00:00
  • Lecture 30 – Operations on Crisp and Fuzzy Relations
    00:00
  • Lecture 29 – Fuzzy Relation 2
    00:00
  • Lecture 13 – Properties of Fuzzy Sets – 2
    00:00
  • Lecture 12 – Properties of Fuzzy Sets – 1
    00:00
  • Lecture 11 – Set Theoretic Operation on Fuzzy Sets
    00:00
  • Lecture 10 – Set Theoretic Operation On Fuzzy Sets
    00:00
  • Lecture 09 – Nomenclatures Used In Fuzzy Set Theory
    00:00
  • Lecture 08 – Nomenclatures Used In Fuzzy Set Theory
    00:00
  • Lecture 07 – Nomenclatures Used In Fuzzy Set Theory
    00:00
  • Lecture 06 – Membership Functions- ll
    00:00
  • Lecture 5: Membership Functions
    00:00
  • Lecture 4: Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB – II
    00:00
  • Lecture 3: Fuzzy Sets and Fuzzy Logic Toolbox in MATLAB
    00:00
  • Lecture 2: Introduction: Real Life Applications of Fuzzy Systems
    00:00
  • Lecture 1:Introduction: Fuzzy Sets, Logic and Systems & Applications
    00:00
  • Lecture 14 – Properties of Fuzzy Sets – 3
    00:00
  • Lecture 15 – Properties of Fuzzy Sets – 4
    00:00
  • Lecture 28 – Fuzzy Relation
    00:00
  • Lecture 27 – Parameterized S-norm Operators
    00:00
  • lecture 26 – Parameterized T-norm Operators
    00:00
  • Lecture 25 – S-norm Operators
    00:00
  • Lecture 24 – T-norm Operators
    00:00
  • Lecture 23 – Compement of Fuzzy Sets
    00:00
  • Lecture 22 – Arithmetic Operations on Fuzzy Numbers – 2
    00:00
  • Lecture 21 – Arithmetic Operations on Fuzzy Numbers
    00:00
  • Lecture 20 – Arithmetic Operations on Fuzzy Numbers
    00:00
  • Lecture 19 – Distance between Fuzzy Sets – 3
    00:00
  • Lecture 18 – Distance between Fuzzy Sets – 2
    00:00
  • Lecture 17 – Distance between Fuzzy Sets
    00:00
  • Lecture 16 – Properties of Fuzzy Sets
    00:00
  • Course Overview
    03:10

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