{"id":5783,"date":"2020-02-08T07:46:49","date_gmt":"2020-02-08T07:46:49","guid":{"rendered":"https:\/\/www.inspirenignite.com\/up\/applied-fuzzy-electronic-systems-ie-7th-sem-syllabus-for-aktu-b-tech-2019-20-scheme-departmental-elective-iv\/"},"modified":"2020-02-08T07:46:49","modified_gmt":"2020-02-08T07:46:49","slug":"applied-fuzzy-electronic-systems-ie-7th-sem-syllabus-for-aktu-b-tech-2019-20-scheme-departmental-elective-iv","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/up\/applied-fuzzy-electronic-systems-ie-7th-sem-syllabus-for-aktu-b-tech-2019-20-scheme-departmental-elective-iv\/","title":{"rendered":"Applied Fuzzy Electronic Systems IE 7th Sem Syllabus for AKTU B.Tech 2019-20 Scheme (Departmental Elective-IV)"},"content":{"rendered":"

Applied Fuzzy Electronic Systems detail syllabus for Instrumentation Engineering (IE), 2019-20 scheme is taken from AKTU<\/a> official website and presented for AKTU students. The course code (REC077), and for exam duration, Teaching Hr\/Week, Practical Hr\/Week, Total Marks, internal marks, theory marks, and credits do visit complete sem subjects post given below.<\/p>\n

For all other ie 7th sem syllabus for b.tech 2019-20 scheme aktu you can visit IE 7th Sem syllabus for B.Tech 2019-20 Scheme AKTU Subjects<\/a>. For all other Departmental Elective-IV subjects do refer to Departmental Elective-IV<\/a>. The detail syllabus for applied fuzzy electronic systems is as follows.<\/p>\n

Unit I<\/h4>\n

For the complete syllabus, results, class timetable and more kindly download iStudy<\/a>. It’s a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.<\/b><\/p>\n

Unit II<\/h4>\n

Fuzzy Rules: Fuzzy Mapping Rule, Fuzzy Implication Rule, Fuzzy Rule Based Models for Function Approximations, Theoretical Foundation of Fuzzy Mapping Rules, Types of Fuzzy Rule Based Models: Mamdani Model, TSK Model, Standard Additive Model, Fuzzy Implications and Approximate Reasoning: Propositional Logic, First Order Predicate Calculus, Fuzzy Implications, Approximate Reasoning, Criteria and Family of Fuzzy Implications, Possibility vs. Probability, Probability of Fuzzy Event, Probabilistic Interpretations of Fuzzy Sets, Fuzzy Measure.\n<\/p>\n

Unit III<\/h4>\n

Uncertainty in information; Classical Sets, Fuzzy Sets and their properties; Cardinality of Classical Relations and their properties, The a- Level Set, Cardinality of Fuzzy Relations and their properties; Composition; Tolerance and Equivalence relationship; Membership Functions; Fuzzification and Defuzzification process; Fuzzy to Crisp Conversions; Lambda cuts; Extension
\nPrinciple, Crisp functions and its mapping, Fuzzy functions and its mapping; Fuzzy Numbers; Internal Analysis in Arithmetic\n<\/p>\n

Unit IV<\/h4>\n

For the complete syllabus, results, class timetable and more kindly download iStudy<\/a>. It’s a lightweight, easy to use, no images, no pdfs platform to make student’s life easier.<\/b><\/p>\n

Unit V<\/h4>\n

Fuzzy Logic in Control Engineering: Fundamental Issues in Control Engineering, Control Design Process, Semiformal Aspects of Design Process, Mamdani Architecture of Fuzzy Control, The Sugeno-Takagi Architecture. Fuzzy Logic in Hierarchical Control Architecture, Historical Overview and Reflections on Mamdani’s Approach, Analysis of Fuzzy Control System via Lyapunov’s Direct Method, Linguistic Approach to the analysis of Fuzzy Control System, Parameter Plane Theory of Stability, Takagi-Sugeno-Kang Model Of Stability Analysis.\n<\/p>\n

Course Objectives:<\/h4>\n

Students undergoing this course are expected:<\/p>\n

    \n
  1. To understand Fuzzy Sets, Possibility Distributions.<\/li>\n
  2. To analysis Fuzzy Rule.<\/li>\n
  3. To Be aware of uncertainty in information.<\/li>\n
  4. To learn approximate method of Extension.<\/li>\n
  5. Analysis Fuzzy Logic in Control Engineering.<\/li>\n<\/ol>\n

    Course Outcomes:<\/h4>\n