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Also, in the recently developed numerical simulation methods, it is tempting to apply the cosine projection to reduce the computational expense.
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In the polydisk we use Riesz projections to reduce the problem to the disk case.
Therefore, Wang et al. [13] proposed sparse random projections to reduce the computational complexity but guarantee that the error probability is comparable to that achieved by the dense random projections.
The current work develops a model for the behaviour of inclusions on the boundary between two phases, exploiting a projection technique to reduce the dimensionality of the problem and thus significantly reduce computational expense by a factor proportional to the ratio of volume to surface area (compared to a uniform volume mesh).
Production, sales and tax receipts are likely to increase for years to come.As a signatory to a World Health Organisation tobacco-control treaty, China is, rather awkwardly in the face of these projections, meant to reduce smoking.
Financial analysts had expected DaimlerChrysler to revise its 2002 projection down and to reduce the dividend, but they were somewhat surprised by the extent of both.
It is convenient to perform some stereographic projection in order to reduce the above problem to R + n.
In terms of compressed sensing theory, random projection is introduced to reduce the feature dimension in [9,10].
Although all individual images can be saved, we stored and analyzed 2D projection images only to reduce data storage space and image analysis time.
As a first step, a projection method is used to reduce the problem to a regular abstract inverse problem.
After the support of the sparse signal is recovered, the projection measurement is designed to reduce the mean squared error of the estimated sparse signal.
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