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20122026
most citedConstructive sparse trigonometric approximation for functions with small mixed smoothness

12 citations · 38 across the 10 of their papers we have counts for

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math.NA2026

Some theoretical and practical results on noisy signals recovery

M. Makurin, Yu. Malykhin, K. Ryutin +1

We discuss some theoretical results and their applications to specific practical problems from wireless communications. We assume that we know the noisy version of the signal, whic…

math.NA2024★ 1 cited

One-sided discretization inequalities and sampling recovery

Irina Limonova, Yuri Malykhin, Vladimir Temlyakov

Recently, in a number of papers it was understood that results on sampling discretization and on the universal sampling discretization can be successfully used in the problem of sa…

math.NA2023

On universal sampling recovery in the uniform norm

V. N. Temlyakov

It is known that results on universal sampling discretization of the square norm are useful in sparse sampling recovery with error measured in the square norm. In this paper we dem…

math.NA2017★ 8 cited

Dispersion of the Fibonacci and the Frolov point sets

V. N. Temlyakov

It is proved that the Fibonacci and the Frolov point sets, which are known to be very good for numerical integration, have optimal rate of decay of dispersion with respect to the c…

math.NA2017★ 6 cited

The Marcinkiewicz-type discretization theorems

V. N. Temlyakov

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. This problem is very important in applications but there is no syste…

math.NA2015★ 12 cited

Constructive sparse trigonometric approximation for functions with small mixed smoothness

V. N. Temlyakov

The paper gives a constructive method, based on greedy algorithms, that provides for the classes of functions with small mixed smoothness the best possible in the sense of order ap…