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Titlebook: Synergetic Computers and Cognition; A Top-Down Approach Hermann Haken Textbook 19911st edition Springer-Verlag Berlin Heidelberg 1991 Syne

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書目名稱Synergetic Computers and Cognition
副標(biāo)題A Top-Down Approach
編輯Hermann Haken
視頻videohttp://file.papertrans.cn/885/884161/884161.mp4
叢書名稱Springer Series in Synergetics
圖書封面Titlebook: Synergetic Computers and Cognition; A Top-Down Approach  Hermann Haken Textbook 19911st edition Springer-Verlag Berlin Heidelberg 1991 Syne
描述This book will be of interest to graduate students, researchers and teachers in the computer sciences, in the cognitive sciences andin physics. It provides the reader with a novel approach to the design and study of neural nets. The applicability of this approach is shown explicitly by means of realistic examples. In addition, detailed models of the cognitive abilities of humans are included and compared with the performance of the synergetic computer presented in this book. The work presented here would not have been possible without the important help of my coworkers. Dr. Arne Wunderlin has helped me in many respects over many years and has made essential contributions, in particular to the slaving principle of synergetics. Drs. Michael Bestehorn, Rudolf Friedrich and Wolfgang W eimer have applied the methods of synergetics to spontaneous pattern forma- tion in fluids and have further developed these methods. Armirr Fuchs has not only implemented my algorithm on a VAX computer, but has also made his own important contributions, in particular to pattern recognition that is invariant with respect to translation, rotation, and scaling. Thomas Ditzinger, Richard Haas, and Robert H?nl
出版日期Textbook 19911st edition
關(guān)鍵詞Synergetic Computer; algorithms; associative memory; cognition; equilibrium; invariant; learning; learning
版次1
doihttps://doi.org/10.1007/978-3-662-22450-2
isbn_ebook978-3-662-22450-2Series ISSN 0172-7389 Series E-ISSN 2198-333X
issn_series 0172-7389
copyrightSpringer-Verlag Berlin Heidelberg 1991
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The Standard Model of Synergetics for Pattern Recognitionorder to construct our model, we use three ingredients:
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Possible Realizations by NetworksIn Chaps. 5 and 6 we presented our general algorithm for the recognition of patterns. This algorithm exploited strong analogies between pattern formation and pattern recognition as unearthed by synergetics. In this chapter we wish to show how this algorithm can be also implemented on a network which acts in a highly parallel manner.
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Simultaneous Invariance with Respect to Translation, Rotation and ScalingIn this chapter we wish to show how pattern recognition can be made invariant with respect to the above-mentioned transformations.
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Dynamic Pattern Recognition of Coordinated Biological MotionSo far in this book we have been concerned with static patterns. As humans, we may also recognize patterns of movement such as walking and trotting of horses. This leads us to ask whether movement patterns can also be recognized by the synergetic computer.
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Synergetic Computers and Cognition978-3-662-22450-2Series ISSN 0172-7389 Series E-ISSN 2198-333X
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