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The schematic diagram of ( i^{text{th}} ) independent distribution grid computation is shown as Fig. 3.
Open image in new window Fig. 3 Illustration of the i th independent distribution grid computation model.
The advantage in opting for grid computation is so high that the concept in itself has given rise to challenges that motivate technological advancements in other areas be it web services, patterns (analysis, design or architectural), grid markup language, semantic grid or at the programming level.
Grid computation to test model assumptions is also developed for these two types of models.
We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation.
Since the presence of bump attractors is necessary for grid computation, we tested whether networks with only structured E-E connections can generate activity bumps.
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With our approach we are able to compute accurate solutions using as little as one third the number of grid points as uniform grid computations in the literature.
In this paper we present CAMELotGrid, a tool to manage Grid computations of Cellular Automata that support the efficient simulation of complex systems modeled by a very large number of simple elements (cells) with local interaction only.
The relationship between noise intensity and gamma differed from that for grid computations.
The relationship between gamma and synaptic strength differs to that for grid computations.
Thus, noise can be beneficial for computations performed by the nervous system, while the frequency and power of multiplexed gamma oscillations can be tuned independently of rate-coded grid computations, suggesting a mechanism for differential control of multiplexed neural codes.
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