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Titlebook: Neuroinformatics; Chiquito Joaqium Crasto,Stephen H. Koslow Book 2007 Humana Press 2007 Alzheimer.imaging techniques.neural network.neurob

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21#
發(fā)表于 2025-3-25 05:05:49 | 只看該作者
22#
發(fā)表于 2025-3-25 10:29:59 | 只看該作者
generalized versions of various efficient sparse grid algorithms in a unified notation: For local basis functions, transformations between function values at grid points and interpolation coefficients can be efficiently realized using the well-known unidirectional principle (Balder and Zenger, ., 17
23#
發(fā)表于 2025-3-25 13:59:24 | 只看該作者
24#
發(fā)表于 2025-3-25 16:29:28 | 只看該作者
25#
發(fā)表于 2025-3-25 20:37:01 | 只看該作者
William Bug,Carl Gustafson,Allon Shahar,Smadar Gefen,Yingli Fan,Louise Bertrand,Jonathan Nissanovby finite difference methods, A great deal of effort has been devoted to the design and study of iterative methods for the solution of such linear systems (Varga (1962A), Wachspress (1966A) and Young (1971B)). Among direct methods, i.e. methods which give an exact solution of the finite difference e
26#
發(fā)表于 2025-3-26 01:43:05 | 只看該作者
Kate Fissellthese equations cannot be solved readily by analytical means. Consequently, efficient computer algorithms for the solution of sparse linear systems derived from the finite difference representations of a partial differential equation on a rectangular grid are of vital importance. In this paper, a ne
27#
發(fā)表于 2025-3-26 06:47:12 | 只看該作者
28#
發(fā)表于 2025-3-26 09:00:36 | 只看該作者
29#
發(fā)表于 2025-3-26 15:26:07 | 只看該作者
Managing Knowledge in Neuroscienceing from advances in electronic information technology. We created a program, NeuroText (.), designed specifically to extract information relevant to neuroscience-specific databases, NeuronDB and CellPropDB (.), housed at the Yale University School of Medicine. NeuroText extracts relevant informatio
30#
發(fā)表于 2025-3-26 16:58:58 | 只看該作者
Interoperability Across Neuroscience Databasesience, robust data interoperability is more difficult to achieve due to data heterogeneity, continuous domain changes, and the constant creation of new semantic data models (Nadkarni et al., . 6, 478–93, 1999; Miller et al., . 8, 34–48, 2001; Gardner et al., . 8, 17–33, 2001). Data heterogeneity in
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