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Introduction
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Publications
Publications (5)
In this paper we have constructed the goodness-of-fit tests incorporating several components, like expectation and covariance function for identification of a non-centered univariate random sequence or auto-covariances and cross-covariances for identification of a centered multivariate random sequence. For the construction of the corresponding esti...
A new approach to the signal processing called compressive sensing has been extensively developed during the last few years. There are many papers devoted to this topic but the problem of constructing the universal measurement matrix has not yet been solved. We propose to use a matrix whose entries are random variables belonging to some Orlicz spac...
In this paper, we consider a continuous in mean square homogeneous and isotropic Gaussian random field. A criterion for testing hypotheses about the covariance function of such field using estimates for its norm in the space $L_p(\mathbb{T}), p\geq 1$ is constructed.
We consider a measurable stationary Gaussian stochastic process. A criterion
for testing hypotheses about the covariance function of such a process using
estimates for its norm in the space $L_p(\mathbb {T}),\,p\geq1$, is
constructed.
The aim of this article is to construct the generalized random matrices, which satisfies the restricted isometry property (as introduced by Candes and Tao). Let the data be presented as a product of a vector with not more than K nonzero coordinates by a given matrix. We show that for such data we can change the upper bound of the variable K. In par...
