SOFT COMPUTING ( Elective II) [VII Semester ECE]

Author: I.A.Dhotre "VII Semester ECE"

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Publisher	Technical Publications
Product Format	Paper Back
Language Published	English
Volume Number	--
Number of Pages	--
Product ID	9789333206839

SOFT COMPUTING ( Elective II) :

UNIT I INTRODUCTION

Artificial neural network: Introduction, Characteristics - Learning methods - Taxonomy - Evolution of neural networks - Basic models - Important technologies - Applications. Fuzzy logic: Introduction - crisp sets- fuzzy sets - crisp relations and fuzzy relations: cartesian product of relation - classical relation, fuzzy relations, tolerance and equivalence relations, non-iterative fuzzy sets. Genetic algorithm- Introduction - biological background - traditional optimization and search techniques - Genetic basic concepts.

UNIT II NEURAL NETWORKS

McCulloch-Pitts neuron - Linear separability - Hebb network - Supervised learning network: perceptron networks - Adaptive linear neuron, Multiple adaptive linear neuron, BPN, RBF, TDNN - Associative memory network: Auto-associative memory network, hetero-associative memory network, BAM, hopfield networks, Iterative autoassociative memory network & iterative associative memory network - unsupervised learning networks: Kohonen self organizing feature maps, LVQ - CP networks, ART network.

UNIT III FUZZY LOGIC

Membership functions: features, fuzzification, methods of membership value assignments - Defuzzification: lambda cuts - Methods - Fuzzy arithmetic and fuzzy measures: fuzzy arithmetic - Extension principle - Fuzzy measures - Measures of fuzziness - Fuzzy integrals - Fuzzy rule base and approximate reasoning : truth values and tables, fuzzy propositions, formation of rules-decomposition of rules, aggregation of fuzzy rules, fuzzy reasoning-fuzzy inference systems-overview of fuzzy expert system fuzzy decision making.

UNIT IV GENETIC ALGORITHM

Genetic algorithm and search space - General genetic algorithm - Operators - Generational cycle - Stopping condition - Constraints - Classification - Genetic programming - Multilevel optimization - Real life problem - Advances in GA

UNIT V HYBRID SOFT COMPUTING TECHNIQUES & APPLICATIONS

Neuro-fuzzy hybrid systems - Genetic neuro hybrid systems - Genetic fuzzy hybrid and fuzzy genetic hybrid systems - Simplified fuzzy ARTMAP - Applications: A fusion approach of multispectral images with SAR, optimization of traveling salesman problem using genetic algorithm approach, soft computing based hybrid fuzzy controllers.