This book gives a systemic account of major concepts, methodologies of artificial neural networks and to present a unified frame work that makes the subject more accessible to students and practitioners. The book emphasizes fundamental theoretical aspects of the computational capabilities and learning abilities of artificial neural networks. It integrates important theoretical results on artificial neural networks and uses them to explain a wide range of existing empirical observations and commonly used heuristics. The main audience of the book is undergraduate students in electrical engineering, computer science and engineering. It can also be used as a valuable resource for practical engineering, computer scientists and others involved in research of artificial neural networks

� propos des auteurs:

Dr C Naga Bhaskar Ph.D is Professor and Principal, NRI Institute of Technology, Vijayawada. He has a vast teaching and research experience for the last 20 years. He has been awarded various National scholarships and fellowships during his academic and research career. He has large number of publications in International and National journals. He was awarded Best Teacher Award by JNTU Kakinada. He has guided several UG, PG and Ph.D Students. His areas of interest include Computational Fluid Mechanics.

G Vijay Kumar is Associate Professor and Head of Department of CSE in VKR, VNB and AGK Engineering College, Gudivada. He is pursuing Ph.D from SCSVMV University, Kanchi. He has 11 years of experience in teaching and research. He is a member of AMIETE, MISTE, MBMESI. He has been awarded as YOUNG TEACHER by AICTE, New Delhi under CAYT Scheme. He published papers in journal and conferences at National and International level. His areas of interest include Neural Networks, Computer Networks, Operating Systems, Communication Systems and Image Processing.

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Articles li�s � Neural Networks and Fuzzy Logic

Neural Networks and Fuzzy Logic

Naga Bhaskar; Vijay Kumar, G

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