Titlebook: Computational Neuroscience; Wanpracha Chaovalitwongse,Panos M. Pardalos,Petros Book 2010 Springer Science+Business Media, LLC 2010 Master

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Computational Neuroscience978-0-387-88630-5Series ISSN 1931-6828 Series E-ISSN 1931-6836

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1931-6828 state-of-the-art account of recent developments in the fiel.This book represents a collection of recent advances in computational studies in neuroscience research that practically applies to a collaborative and integrative environment in engineering and medical domains. This work has been designed

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Britain and Britishness at the Crossroads,ps were employed. The results show that although .NN and linear SVM can classify active and nonactive voxels with less than 1.2% error, careful preprocessing of the data, including dimensionality reduction, outlier elimination, and denoising are important factors in overall classification.

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Comparison of Supervised Classification Methods with Various Data Preprocessing Procedures for Activps were employed. The results show that although .NN and linear SVM can classify active and nonactive voxels with less than 1.2% error, careful preprocessing of the data, including dimensionality reduction, outlier elimination, and denoising are important factors in overall classification.

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