Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition
In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Get and download textbook Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition for free
author sandhya samarasinghe format hardback language english publication year 12 09 2006 subject computing it subject 2 computing professional programming title neural networks for applied sciences and engineering from fundamentals to complex pattern recognition author samarasinghe sandhya author publisher auerbach pub publication date sep 15 2006 pages 570 binding hardcover edition 1 st dimensions 6 25 wx 9 25 hx 1 50 d isbn 084933375 x subject computers programming systems analysis design de
Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage on linear networks, as well as, multi-layer perceptron for nonlinear prediction and classification explaining all stages of processing and model development illustrated through Neural Networks for Applied Sciences and Engineering new edition
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Neural Networks for Applied Sciences and Engineering From Fundamentals to Complex Pattern Recognition, ISBN-13: 9780849333750, ISBN-10: 084933375X
Author: Samarasinghe, Sandhya ISBN-10: 084933375X
Taylor & Francis Ltd | 2006 | 570 pages | ISBN-13: 9780849333750 | ISBN-10: 084933375X | You save 10%
"In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks. Beginning with an introductory discussion on the role of neural networks in scientific data analysis, this book provides a solid foundation of basic neural network concepts. It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage on linear networks, as well as
Neural Networks for Applied Sciences and Engineering Textbook
It contains an overview of neural network architectures for practical data analysis followed by extensive step-by-step coverage on linear networks, as well as, multi-layer perceptron for nonlinear prediction and classification explaining all stages of processing and model development illustrated through
