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Titlebook: Hybrid Neural Systems; Stefan Wermter,Ron Sun Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 2000 Fuzzy.Neural systems.algo

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書目名稱Hybrid Neural Systems
編輯Stefan Wermter,Ron Sun
視頻videohttp://file.papertrans.cn/431/430151/430151.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Hybrid Neural Systems;  Stefan Wermter,Ron Sun Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 2000 Fuzzy.Neural systems.algo
描述Hybrid neural systems are computational systems which are based mainly on artificial neural networks and allow for symbolic interpretation or interaction with symbolic components. This book is derived from a workshop held during the NIPS‘98 in Denver, Colorado, USA, and competently reflects the state of the art of research and development in hybrid neural systems..The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches.
出版日期Conference proceedings 2000
關(guān)鍵詞Fuzzy; Neural systems; algorithmic learning; artificial neural networks; classification; cognitive scienc
版次1
doihttps://doi.org/10.1007/10719871
isbn_softcover978-3-540-67305-7
isbn_ebook978-3-540-46417-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2000
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Alan B. Tickle,Frederic Maire,Guido Bologna,Robert Andrews,Joachim Diederichung solcher Strukturen als Voraussetzung für eine sp?tere Segmentierung werden Verfahren benutzt, die in Analogie zur Signalverarbeitung als . oder im englischen Sprachgebrauch zutreffender als . bezeichnet werden. Diese Verfahren stammen zu einem gro?en Teil aus der Physik, aber auch aus den Ingeni
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A Connectionist Simulation of the Empirical Acquisition of Grammatical Relationser. This leads to the notion that grammatical relations are learned in a bottom up fashion. Combining this theoretical position with the notion that the main purpose of language is communication, we demonstrate the emergence of the notion of “subject” in a simple recurrent network that learns to map
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https://doi.org/10.1007/10719871Fuzzy; Neural systems; algorithmic learning; artificial neural networks; classification; cognitive scienc
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A Recursive Neural Network for Reflexive Reasoning to be sound and complete if only unary relation symbols are involved and complete but unsound otherwise. For the latter case a criteria is defined which guarantees correctness. Finally, we compare our system to the forward reasoning version of ..
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