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Recurrent Neural Networks
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Recurrent Neural Networks

Recurrent Neural Networks

Larry Medsker

392 pages, parution le 20/02/2000

Résumé

With existent uses ranging from motion detection to music synthesis
to financial forecasting, recurrent neural networks have generated widespread
attention. The tremendous interest in these networks drives Recurrent Neural
Networks: Design and Applications
, a summary of the design, applications,
current research, and challenges of this subfield of artificial neural networks.
This overview incorporates every aspect of recurrent neural networks. It
outlines the wide variety of complex learning techniques and associated research
projects. Each chapter addresses architectures, from fully connected to
partially connected, including recurrent multilayer feedforward. It presents
problems involving trajectories, control systems, and robotics, as well as RNN
use in chaotic systems. The authors also share their expert knowledge of ideas
for alternate designs and advances in theoretical aspects.

The dynamical behavior of recurrent neural networks is useful for solving
problems in science, engineering, and business. This approach will yield huge
advances in the coming years. Recurrent Neural Networks illuminates the
opportunities and provides you with a broad view of the current events in this
rich field.

Caractéristiques techniques

  PAPIER
Éditeur(s) Chapman and Hall / CRC
Auteur(s) Larry Medsker
Parution 20/02/2000
Nb. de pages 392
EAN13 9780849371813

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