Principles of Artificial Neural Networks: 3rd Edition (Advanced Series in Circuits & Systems) (Advanced Series in Circuits and Systems)

By Daniel Graupe

Synthetic neural networks are most fitted for fixing difficulties which are complicated, ill-defined, hugely nonlinear, of many and diverse variables, and/or stochastic. Such difficulties are ample in medication, in finance, in safety and past.

This quantity covers the fundamental conception and structure of the main man made neural networks. Uniquely, it provides 18 entire case stories of purposes of neural networks in a number of fields, starting from cell-shape type to micro-trading in finance and to constellation acceptance all with their respective resource codes. those case experiences exhibit to the readers intimately how such case reviews are designed and carried out and the way their particular effects are bought.

The publication is written for a one-semester graduate or senior-level undergraduate direction on man made neural networks.

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