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The output of the calculations is structured for easy input of the derived 3D distribution into ion optics simulation packages.
A maximum likelihood approach is used to estimate a phylogenetic tree for predicting the most likely structure for input sequences.
One of the primary motivations for providing a highly structured XML input format is to facilitate reproducibility of complex evolutionary analyses.
Participants who had received blocked input during training significantly outperformed those receiving randomly structured input (see Table 6 for a summary of the results of the statistical analyses).
Spike-based learning models for temporally structured input need to take this timing information into account (e.g. Gerstner et al. 1993) which leads to models of spike-timing dependent plasticity (STDP) (Gerstner et al. 1996; Kempter et al. 1999; Roberts 1999; Abbott and Nelson 2000) that can be seen as a spike-based generalization of Hebbian learning.
We would then expect that, for different structured external inputs with similar means, a network might produce population oscillations with the same frequency, but with different groups of neurons firing at the peak of the oscillations.
In this paper we present an algorithm for the all-pairs suffix prefix problem that uses a simple data structure for storing input strings and advanced algorithmic techniques for matching, which together lead to fast running time in practice.
This paper proposed a non-separable 2D structure for 4D input signals in lieu of non-separable 3D structures.
To lower the rounding noise inside the transform, the non-separable 2D structure for 4D input signals is proposed.
This paper proposes a non-separable 2D quadruple lifting structure for 4D input signals to deal with the problem of degradation in image quality due to integer implementation.
The whole process iteratively joins the similar sequences into families and therefore produces a hierarchical structure for the input dataset.
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