PE9275 SOFT COMPUTING TECHNIQUES SYLLABUS | ANNA UNIVERSITY ME EMBEDDED SYSTEM TECHNOLOGIES 1ST SEM SYLLABUS REGULATION 2009 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY FIRST SEMESTER M.E. EMBEDDED SYSTEM TECHNOLOGIES DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI,TIRUNELVELI,COIMBATORE), 2009 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
PE9275 SOFT COMPUTING TECHNIQUES L T P C
3 0 0 3
UNIT I INTRODUCTION 9
Approaches to intelligent control. Architecture for intelligent control. Symbolic reasoning
system, rule-based systems, the AI approach. Knowledge representation. Expert
systems.
UNIT II ARTIFICIAL NEURAL NETWORKS 9
Concept of Artificial Neural Networks and its basic mathematical model, McCulloch-Pitts
neuron model, simple perceptron, Adaline and Madaline, Feed-forward Multilayer
Perceptron. Learning and Training the neural network. Data Processing: Scaling, Fourier
transformation, principal-component analysis and wavelet transformations. Hopfield
network, Self-organizing network and Recurrent network. Neural Network based
controller
UNIT III FUZZY LOGIC SYSTEM 9
Introduction to crisp sets and fuzzy sets, basic fuzzy set operation and approximate
reasoning. Introduction to fuzzy logic modeling and control. Fuzzification, inferencing
and defuzzification. Fuzzy knowledge and rule bases. Fuzzy modeling and control
schemes for nonlinear systems. Self-organizing fuzzy logic control. Fuzzy logic control
for nonlinear time-delay system.
UNIT IV GENETIC ALGORITHM 9
Basic concept of Genetic algorithm and detail algorithmic steps, adjustment of free
parameters. Solution of typical control problems using genetic algorithm. Concept on
some other search techniques like tabu search and anD-colony search techniques for
solving optimization problems.
UNIT V APPLICATIONS 9
GA application to power system optimisation problem, Case studies: Identification and
control of linear and nonlinear dynamic systems using Matlab-Neural Network toolbox.
Stability analysis of Neural-Network interconnection systems. Implementation of fuzzy
logic controller using Matlab fuzzy-logic toolbox. Stability analysis of fuzzy control
systems.
TOTAL : 45 PERIODS
REFERENCES
1. Jacek.M.Zurada, "Introduction to Artificial Neural Systems", Jaico Publishing
House, 1999.
2. KOSKO,B. "Neural Networks And Fuzzy Systems", Prentice-Hall of India Pvt. Ltd.,
1994.
3. KLIR G.J. & FOLGER T.A. "Fuzzy sets, uncertainty and Information", Prentice-Hall of
India Pvt. Ltd., 1993.
4. Zimmerman H.J. "Fuzzy set theory-and its Applications"-Kluwer Academic
Publishers, 1994.
5. Driankov, Hellendroon, "Introduction to Fuzzy Control", Narosa Publishers.
PE9275 SOFT COMPUTING TECHNIQUES L T P C
3 0 0 3
UNIT I INTRODUCTION 9
Approaches to intelligent control. Architecture for intelligent control. Symbolic reasoning
system, rule-based systems, the AI approach. Knowledge representation. Expert
systems.
UNIT II ARTIFICIAL NEURAL NETWORKS 9
Concept of Artificial Neural Networks and its basic mathematical model, McCulloch-Pitts
neuron model, simple perceptron, Adaline and Madaline, Feed-forward Multilayer
Perceptron. Learning and Training the neural network. Data Processing: Scaling, Fourier
transformation, principal-component analysis and wavelet transformations. Hopfield
network, Self-organizing network and Recurrent network. Neural Network based
controller
UNIT III FUZZY LOGIC SYSTEM 9
Introduction to crisp sets and fuzzy sets, basic fuzzy set operation and approximate
reasoning. Introduction to fuzzy logic modeling and control. Fuzzification, inferencing
and defuzzification. Fuzzy knowledge and rule bases. Fuzzy modeling and control
schemes for nonlinear systems. Self-organizing fuzzy logic control. Fuzzy logic control
for nonlinear time-delay system.
UNIT IV GENETIC ALGORITHM 9
Basic concept of Genetic algorithm and detail algorithmic steps, adjustment of free
parameters. Solution of typical control problems using genetic algorithm. Concept on
some other search techniques like tabu search and anD-colony search techniques for
solving optimization problems.
UNIT V APPLICATIONS 9
GA application to power system optimisation problem, Case studies: Identification and
control of linear and nonlinear dynamic systems using Matlab-Neural Network toolbox.
Stability analysis of Neural-Network interconnection systems. Implementation of fuzzy
logic controller using Matlab fuzzy-logic toolbox. Stability analysis of fuzzy control
systems.
TOTAL : 45 PERIODS
REFERENCES
1. Jacek.M.Zurada, "Introduction to Artificial Neural Systems", Jaico Publishing
House, 1999.
2. KOSKO,B. "Neural Networks And Fuzzy Systems", Prentice-Hall of India Pvt. Ltd.,
1994.
3. KLIR G.J. & FOLGER T.A. "Fuzzy sets, uncertainty and Information", Prentice-Hall of
India Pvt. Ltd., 1993.
4. Zimmerman H.J. "Fuzzy set theory-and its Applications"-Kluwer Academic
Publishers, 1994.
5. Driankov, Hellendroon, "Introduction to Fuzzy Control", Narosa Publishers.
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