Résumé
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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