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Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition | |||||
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Rok: 2006 AnotaceIn response to the increasing demand for novel computing methods, Neural Networks for Applied Sciences and Engineering provides a simple but systematic introduction to neural networks applications. This book features case studies that use real data to demonstrate practical applications. It contains in-depth discussions of data and model validation issues as well as data dimensionality and methods to reduce dimensionality. It provides a detailed coverage of neural networks types for nonilnear patterns in multi-dimensional scientific data and time-series forecasting. In particular, it provides an extensive coverage of all aspects of multi-layer perceptron and self-organization maps- two powerful methods for nonlinear prediciton, classification, and clustreing of complex data. Furthermore, it puts neural networks in the context of linear and nonilnear statistical methods. Dostupné zdroje
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