Download E-books Predictive Modular Neural Networks: Applications to Time Series (The Springer International Series in Engineering and Computer Science) PDF

By Vassilios Petridis

The topic of this publication is predictive modular neural networks and their ap­ plication to time sequence difficulties: class, prediction and identity. The meant viewers is researchers and graduate scholars within the fields of neural networks, machine technological know-how, statistical trend reputation, facts, keep an eye on conception and econometrics. Biologists, neurophysiologists and clinical engineers can also locate this publication attention-grabbing. within the final decade the neural networks group has proven extreme curiosity in either modular equipment and time sequence difficulties. comparable curiosity has been expressed for a few years in different fields besides, so much particularly in statistics, keep watch over conception, econometrics and so on. there's a significant overlap (not consistently famous) of rules and techniques among those fields. Modular neural networks come by means of many different names, for example a number of types, neighborhood types and combinations of specialists. the elemental notion is to independently improve numerous "subnetworks" (modules), which could practice an analogous or re­ lated projects, after which use an "appropriate" process for combining the outputs of the subnetworks. many of the anticipated merits of this strategy (when in comparison with using "lumped" or "monolithic" networks) are: more advantageous functionality, diminished improvement time and bigger flexibility. for example, if a module is faraway from the community and changed through a brand new module (which may well practice an identical job extra efficiently), it's going to no longer be essential to retrain the mixture community.

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