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Titlebook: Computation and Neural Systems; Frank H. Eeckman,James M. Bower Book 1993 Springer Science+Business Media New York 1993 Nervous System.ass

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書目名稱Computation and Neural Systems
編輯Frank H. Eeckman,James M. Bower
視頻videohttp://file.papertrans.cn/233/232050/232050.mp4
圖書封面Titlebook: Computation and Neural Systems;  Frank H. Eeckman,James M. Bower Book 1993 Springer Science+Business Media New York 1993 Nervous System.ass
描述Computational neuroscience is best defined by its focus onunderstanding the nervous systems as a computational device ratherthan by a particular experimental technique. Accordinlgy, while themajority of the papers in this book describe analysis and modelingefforts, other papers describe the results of new biologicalexperiments explicitly placed in the context of computational issues.The distribution of subjects in .Computation and Neural Systems.reflects the current state of the field. In addition to the scientificresults presented here, numerous papers also describe the ongoingtechnical developments that are critical for the continued growth ofcomputational neuroscience...Computation and Neural Systems. includes papers presented at theFirst Annual Computation and Neural Systems meeting held in SanFrancisco, CA, July 26--29, 1992..
出版日期Book 1993
關鍵詞Nervous System; associative memory; computational neuroscience; cortex; learning; memory; modeling; neurosc
版次1
doihttps://doi.org/10.1007/978-1-4615-3254-5
isbn_softcover978-1-4613-6431-3
isbn_ebook978-1-4615-3254-5
copyrightSpringer Science+Business Media New York 1993
The information of publication is updating

書目名稱Computation and Neural Systems影響因子(影響力)




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ular experimental technique. Accordinlgy, while themajority of the papers in this book describe analysis and modelingefforts, other papers describe the results of new biologicalexperiments explicitly placed in the context of computational issues.The distribution of subjects in .Computation and Neura
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https://doi.org/10.1007/978-1-4615-3254-5Nervous System; associative memory; computational neuroscience; cortex; learning; memory; modeling; neurosc
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A Similarity-Based Color Descriptor for Face Detectionrformance is significant and superior to several other color descriptors, which are in use for object detection. This color descriptor can be applied in color-based object detection and recognition tasks.
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