By Daniel Graupe
Synthetic neural networks are best suited for fixing difficulties which are advanced, ill-defined, hugely nonlinear, of many and various variables, and/or stochastic. Such difficulties are plentiful in drugs, in finance, in safety and past.
This quantity covers the elemental concept and structure of the foremost synthetic neural networks. Uniquely, it provides 18 entire case reviews of purposes of neural networks in a variety of fields, starting from cell-shape class to micro-trading in finance and to constellation acceptance all with their respective resource codes. those case reports show to the readers intimately how such case reports are designed and performed and the way their particular effects are received.
The e-book is written for a one-semester graduate or senior-level undergraduate path on synthetic neural networks.
Read Online or Download Principles of Artificial Neural Networks: 3rd Edition (Advanced Series in Circuits & Systems) (Advanced Series in Circuits and Systems) PDF
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