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We develop a representation free stochastic calculus based on three inequalities (semimartingale inequality, scalar forward derivative inequality, scalar conditional variance inequality).
Unlike previous model-based approaches, where speech and non-speech classes were usually modeled by several models, we develop a representation where just one model per class is used in the segmentation process.
To do the latter, one must develop a representation for the underlying scene or phenomenon that is being measured and understand the mapping between that representation and the measurements y1, y2,..., y J.
However, when the structural form itself is unknown, adaptive control relies on structural learning to develop a representation of the control process.
They recommend using imagery and externalising images of the self in order to make connections between thoughts, feelings and memories and to start to develop a representation of the current adult self.
We build upon our previous work [ 29] to detail how a "blank" structure (representing parietal mirror neurons that have seen some previous attention by modelers [ 28, 29]) can develop a representation of its inputs in line with the finding that most but not all neurons encoding a given motion primitive are also sensitive to the goal of the overall action [ 6].
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In order to achieve sufficient performance for practical applicability, we have developed a representation that provides a highly abstracted view of programs and faults, but is sufficiently detailed to yield substantial reductions in the fault localization costs when compared to the current manpower-intensive approach.
Between the World Wars, Herman Wold developed a representation of stationary stochastic processes in terms of autoregressive models and a determinist trend.
Simulation involves developing a representation of this underlying "system".
Here, we have developed a representation method called the voxel model, which has two distinguishing features.
Of importance, as seen with the linear visualization activity, simply seeing the Geologic Time Scale aligned to a spatial linear representation may not be enough to develop a linear representation of geologic magnitude.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com