Sampling -Reconstruction Procedure of Some Non-Gaussian Processes with Jitter

Казаков, Владимир; Osorio, J.; Gonzalez, S.

doi:10.1109/msmw.2007.4294872

Cited by 1 publication

(3 citation statements)

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“…This function is realized in two parts. The first is a special deterministic part of the reconstruction error function generated by a relation between the reconstruction function of the optimal algorithm   t m and the reconstruction function of the quasi optimal algorithm   t m , that is [4]:…”

Section: The Quasi Optimal Reconstruction Algorithmmentioning

confidence: 99%

“…The optimal algorithm continues using the CMR by (2). But the quasi optimal algorithm associates the reconstruction functions of both algorithms by (4). The optimal case does not consider the value of the samples to get the reconstruction error, the quasi optimal case does consider.…”

Section: Comparison Between Both Reconstruction Algorithmsmentioning

confidence: 99%

“…Besides an optimal algorithm, there are many quasi optimal algorithms [4]. For instance, several times there is not enough information about the random process (or their realizations) to reconstruct it, specifically the value of the samples.…”

Section: Introductionmentioning

confidence: 99%

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Quasi optimal reconstruction algorithm based on the clipping for Gaussian processes

Olvera¹

2017

imf

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A quasi optimal reconstruction algorithm based on the clipping is analyzed for Sampling-Reconstruction Procedure of realizations that compose a Gaussian process. Clipping means that it knows just the zero crossings in the realization. To find out its effectiveness, it is compared with an optimal algorithm, which considers some samples of the realization located at strategic points. Results show that the quasi optimal algorithm does not give a correct reconstruction. Hence, it is necessary to include a new parameter within this methodology to improve the performance, mainly reflected in the reconstruction error. However, the quasi optimal algorithm is just an approximations to the optimal algorithm.

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Section: The Quasi Optimal Reconstruction Algorithmmentioning

confidence: 99%

Section: Comparison Between Both Reconstruction Algorithmsmentioning

confidence: 99%