{"product_id":"9781441951588","title":"Artificial Neural Networks for Modelling and Control of Non-Linear Systems","description":"\u003ch1\u003eArtificial Neural Networks for Modelling and Control of Non-Linear Systems\u003c\/h1\u003e \u003ch2\u003eSuykens, Johan A.K.; Vandewalle, Joos P.L.; de Moor, B.L.\u003c\/h2\u003e \u003cp\u003eArtificial neural networks possess several properties that make  them particularly attractive for applications to modelling and control  of complex non-linear systems. Among these properties are their  universal approximation ability, their parallel network structure and  the availability of on- and off-line learning methods for the  interconnection weights. However, dynamic models that contain neural  network architectures might be highly non-linear and difficult to  analyse as a result. \u003cem\u003eArtificial Neural Networks for Modelling  and\u003c\/em\u003e \u003cem\u003eControl of Non-Linear Systems\u003c\/em\u003e investigates the subject  from a system theoretical point of view. However the mathematical  theory that is required from the reader is limited to matrix calculus,  basic analysis, differential equations and basic linear system theory.  No preliminary knowledge of neural networks is explicitly required.  \u003cbr\u003e  The book presents both classical and novel network architectures and  learning algorithms for modelling and control. Topics include  non-linear system identification, neural optimal control, top-down  model based neural control design and stability analysis of neural  control systems. A major contribution of this book is to introduce  \u003cem\u003eNLq\u003c\/em\u003e \u003cem\u003eTheory\u003c\/em\u003e as an extension towards modern control theory,  in order to analyze and synthesize non-linear systems that contain  linear together with static non-linear operators that satisfy a sector  condition: neural state space control systems are an example.  Moreover, it turns out that \u003cem\u003eNLq Theory\u003c\/em\u003e is unifying with respect  to many problems arising in neural networks, systems and control.  Examples show that complex non-linear systems can be modelled and  controlled within NLq theory, including mastering chaos. \u003cbr\u003e  The didactic flavor of this book makes it suitable for use as a text  for a course on Neural Networks. In addition, researchers and  designers will find many important new techniques, in particular  \u003cem\u003eNLq\u003cem\u003eTheory\u003c\/em\u003e, that have applications in control theory,  system theory, circuit theory and Time Series Analysis.\u003c\/em\u003e\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2010-12-07\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003e ISBN-10: 9781441951588\u003c\/p\u003e \u003cp\u003eISBN-13: 9781441951588\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4757-2493-6\u003c\/p\u003e \u003cp\u003eDimensions: 240cm x160cm\u003c\/p\u003e \u003cp\u003ePages: 235\u003c\/p\u003e ","brand":"Springer","offers":[{"title":"Default Title","offer_id":44341312684172,"sku":"9781441951588","price":153.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781441951588.jpg?v=1755042140","url":"https:\/\/lateknightbooks.com\/products\/9781441951588","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}