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Titlebook: Mechanisms, Symbols, and Models Underlying Cognition; First International José Mira,José R. álvarez Conference proceedings 2005 Springer-V

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書目名稱Mechanisms, Symbols, and Models Underlying Cognition
副標(biāo)題First International
編輯José Mira,José R. álvarez
視頻videohttp://file.papertrans.cn/629/628780/628780.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Mechanisms, Symbols, and Models Underlying Cognition; First International  José Mira,José R. álvarez Conference proceedings 2005 Springer-V
出版日期Conference proceedings 2005
關(guān)鍵詞Augmented Reality; SPIN; Simulation; artificial neural networks; automata; bio-inspired computing; brain-l
版次1
doihttps://doi.org/10.1007/b137289
isbn_softcover978-3-540-26298-5
isbn_ebook978-3-540-31672-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2005
The information of publication is updating

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Modules, Layers, Hierarchies, and Loops Where Artificial Intelligence Meets Ethology and Neuroscienccommonalities that underly the understanding of action selection in different disciplines, and that may constitute the pieces of a common language with which AI can communicate ideas and findings to and from ethology and neuroscience.
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Simulation of Orientation Contrast Sensitive Cell Behavior in TiViPEfunctional behavior of the neuronal responses of non orientation (within the CRF) sensitive 4C. cells [5], and give an explanation of the indirect information flow in V1 that explains the behavior of orientation contrast sensitivity.
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Separation of Extracellular Spikes: When Wavelet Based Methods Outperform the Principle Component Anl method of spike features extraction based on a combination of the PCA and continuous WT. Our approach allows automatic tuning of the wavelet part of the method by the use of knowledge obtained from the PCA. To illustrate the methods strength and weakness we provide comparative examples of their performances using simulated and experimental data.
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Gaussian Processes and Neuronal Modelingehavior of first passage time densities for Gaussian processes, both of a Markov and of a non-Markov type. Significant similarities or diversities between computational and simulated results are pointed out.
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