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.
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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.
Processes which are heavily non-linear and/or very complex pose a problem for automatic control, yet they can often be handled easily by human operators. This book describes results from 10 years of research on learning control loops which imitate these human abilities. After discussing the contrast with adaptive control, the authors present some background on human information processing and behaviour. A neuronally-inspired memory layout and a mathematically inspired one are compared and it is shown that they learn much faster than back-propagation neural networks. Different architectures are given for the learning control loop. Their usefulness is demonstrated by simulation and results from applications to real pilot plants. The book should be of interest to control engineers as well as researchers in neural net applications and/or artificial intelligence.
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Softcover. Condición: Très bon. Ancien livre de bibliothèque. Petite(s) trace(s) de pliure sur la couverture. Légères traces d'usure sur la couverture. Couverture différente. Edition 1992. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slightly creased cover. Slight signs of wear on the cover. Different cover. Edition 1992. Ammareal gives back up to 15% of this item's net price to charity organizations. Nº de ref. del artículo: E-812-893
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Softcover. Condición: Très bon. Ancien livre de bibliothèque. Petite(s) trace(s) de pliure sur la couverture. Légères traces d'usure sur la couverture. Pages cornées. Couverture différente. Edition 1992. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritat ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slightly creased cover. Slight signs of wear on the cover. Dog-eared pages. Different cover. Edition 1992. Ammareal gives back up to 15% of this item's net price to charity organizations. Nº de ref. del artículo: E-812-892
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Since heavily non-linear and/or very complex processes stillpose a problem for automatic control, they can often behandled easily by human operators. The book describes results from ten years of research on learning control loopswhich imitate these abilities. After discussing the differencesto adaptive control some background on human information processing and behaviour is put forward and some learning control loop structure related to these ideas is shown.The ability to learn is due to memories, which are able tointerpolate for multi-dimensional input spaces between scattered output values. A neuronally and mathematically inspired memory lay out-are compared and it is shown that theylearn much faster thanbackpropagation neural networkswhich can also be used. For the learning control loop different architectures are given. Their usefulness is demonstrated by simulation and results from applications to real pilot plants. The book should be of interest for control engineers as well as researchers in neural net applicationsand/or artificial intelligence. The usual mathematical background of engineers is sufficient. 228 pp. Englisch. Nº de ref. del artículo: 9783540550570
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Since heavily non-linear and/or very complex processes stillpose a problem for automatic control, they can often behandled easily by human operators. The book describes results from ten years of research on learning control loopswhich imitate these abilities. After discussing the differencesto adaptive control some background on human information processing and behaviour is put forward and some learning control loop structure related to these ideas is shown.The ability to learn is due to memories, which are able tointerpolate for multi-dimensional input spaces between scattered output values. A neuronally and mathematically inspired memory lay out-are compared and it is shown that theylearn much faster thanbackpropagation neural networkswhich can also be used. For the learning control loop different architectures are given. Their usefulness is demonstrated by simulation and results from applications to real pilot plants. The book should be of interest for control engineers as well as researchers in neural net applicationsand/or artificial intelligence. The usual mathematical background of engineers is sufficient. Nº de ref. del artículo: 9783540550570
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Basic considerations.- Microintelligence.- Macrointelligence.Processes which are heavily non-linear and/or very complex pose a problem for automatic control. Yet they can often be handled easily by human operators. This book describes results from ten y. Nº de ref. del artículo: 4893439
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Taschenbuch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch. Nº de ref. del artículo: 9783540550570
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