Name: neurocontrol: learning control systems inspired by neuronal architectures and human problem solving strategies (en Inglés)
SKU: 24728527
Price: 59.46 USD
Availability: InStock
Author: Tolle, H. ; Ersü, E.
ISBN: 9783540550570

portada neurocontrol: learning control systems inspired by neuronal architectures and human problem solving strategies (en Inglés)

neurocontrol: learning control systems inspired by neuronal architectures and human problem solving strategies (en Inglés)

Formato

Libro Físico

Autor

H. Tolle

E. Ersü

Editorial

Springer

Año

1992

Idioma

Inglés

N° páginas

214

Encuadernación

Tapa Blanda

Dimensiones

24.4x17x1.2 cm

Peso

0.37 kg.

ISBN

3540550577

ISBN13

9783540550570

Categorías

Ingeniería eléctrica
Robótica
Inteligencia artificial

neurocontrol: learning control systems inspired by neuronal architectures and human problem solving strategies (en Inglés)

H. Tolle (Autor) · E. Ersü (Autor) · Springer · Tapa Blanda

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Reseña del libro "neurocontrol: learning control systems inspired by neuronal architectures and human problem solving strategies (en Inglés)"

Since heavily non-linear and/or very complex processes still pose a problem for automatic control, they can often be handled easily by human operators. The book describes re- sults from ten years of research on learning control loops, which imitate these abilities. After discussing the diffe- rencesto adaptive control some background on human informa- tion processing and behaviour is put forward and some lear- ning control loop structure related to these ideas is shown. The ability to learn is due to memories, which are able to interpolate for multi-dimensional input spaces between scat- tered output values. A neuronally and mathematically inspi- red memory lay out-are compared and it is shown that they learn much faster thanbackpropagation neural networks, which can also be used. For the learning control loop diffe- rent architectures are given. Their usefulness is demonstra- ted by simulation and results from applications to real pi- lot plants. The book should be of interest for control engi- neers as well as researchers in neural net applications and/or artificial intelligence. The usual mathematical back- ground of engineers is sufficient.