000			01811nam a22002057a 4500
003			CUTN
005			20180920124120.0
008			180920b xxu||||| |||| 00| 0 eng d
020			_a9788120312531
041			_aEnglish
082			_a006.32 _bYEN
100			_aYegnanarayana, B.
245			_aArtificial neural networks _cB. Yegnanarayana
260			_aNew Delhi : _bPHI Learning, _c2015.
300			_axiii, 461 p.: _c22 cm.
505			_tBasics of Artificial Neural Networks _tActivation and Synaptic Dynamics _tFunctional Units of ANN for Pattern Recognition Tasks _tFeedforward Neural Networks _tFeedback Neural Networks _tCompetitive Learning Neural Networks _tArchitectures for Complex Pattern Recognition Tasks _tApplications of ANN
650			_aNeural networks (Computer science)
942			_2ddc _cBOOKS
520			_aDesigned as an introductory level textbook on Artificial Neural Networks at the postgraduate and senior undergraduate levels in any branch of engineering, this self-contained and well-organized book highlights the need for new models of computing based on the fundamental principles of neural networks. Professor Yegnanarayana compresses, into the covers of a single volume, his several years of rich experience, in teaching and research in the areas of speech processing, image processing, artificial intelligence and neural networks. He gives a masterly analysis of such topics as Basics of artificial neural networks, Functional units of artificial neural networks for pattern recognition tasks, Feedforward and Feedback neural networks, and Archi-tectures for complex pattern recognition tasks. Throughout, the emphasis is on the pattern processing feature of the neural networks. Besides, the presentation of real-world applications provides a practical thrust to the discussion.
999			_c25853 _d25853