Pavel Zheltov

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In this paper we show that for dictionaries with small coherence in a Hilbert space the Orthogonal Greedy Algorithm (OGA) performs almost as well as the best m−term approximation for all signals with sparsity almost as high as the best theoretically possible threshold s = 1 2 (M−1 + 1) by proving a Lebesgue-type inequality for arbitrary signals. On the(More)
Based on the here developed functional analytic machinery we extend the theory of operator sampling and identification to apply to operators with stochastic spreading functions. We prove that identification with a delta train signal is possible for a large class of stochastic operators that have the property that the autocorrelation of the spreading(More)
We develop sampling methodology aimed at identifying stochastic operators that satisfy a support size restriction on the autocorrelation of the operators stochastic spreading function. The data that we use to reconstruct the operator (or, in some cases only the autocorrelation of the spreading function) is based on the response of the unknown operator to a(More)
This paper addresses the problem of stochastic radar target measurement. We develop an algorithm that allows for the reconstruction of the scattering function of a WSSUS radar target from the autocorrelation of the response of the target to a deterministic sounding signal. While conventional methods are applicable only when the scattering function is(More)
In many radar scenarios, the radar target or the medium is assumed to possess randomly varying parts. The properties of the target are described by a random process known as the spreading function. Its second order statistics under the WSSUS assumption are given by the scattering function. Recent developments in operator sampling theory suggest novel(More)
In many radar scenarios, the radar target or the medium is assumed to possess randomly varying parts. The properties of a target are described by a random process known as the spreading function. Its second order statistics under the WSSUS assumption are given by the scattering function. Recent developments in the operator identification theory suggest a(More)
ABSTRACT. In many radar scenarios, the radar target or the medium is assumed to possess randomly varying parts. The properties of a target are described by a random process known as the spreading function. Its second order statistics under the WSSUS assumption are given by the scattering function. Recent developments in the operator identification theory(More)
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