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Nurzhan A. Bokayev

Publications and source records attributed to Nurzhan A. Bokayev.

3 recordsLinked to original sources

Characterization of the boundedness of the discrete Fractional maximal operator between weighted in Lorentz sequence spaces

In this paper, we give the complete characterization of the boundedness of the discrete fractional maximal operator $M_γ$, defined on $\mathbb{Z}^n$, $n\in\mathbb{N}$, $γ\in [0,n)$, between the classical Lorentz sequence spaces $λ_p(v)$ and $λ_q(w)$, where $0<p,q<\infty$, $\{v(m)\}$ and $\{w(m)\}$ are non-negative sequences defined on $\mathbb{N}$. We first obtain a sharp upper estimate for the nonincreasing rearrangement of the discrete fractional maximal operator $M_γx$, with a supremal operator involving a discrete Hardy operator and the nonincreasing rearrangement of the sequence $\{x(k)\}$, and we show that this estimate is sharp by showing a lower estimate for special sequences. Using this result, we can reduce the characterization of the boundedness of the discrete fractional maximal operator $ M_γ$ between the discrete weighted Lorentz sequence spaces to the boundedness of the discrete supremum operator between weighted Lebesgue sequence spaces, restricted to nonincreasing sequences. This problem was investigated in the authors' recent paper, which enables us to obtain the final characterization.

math.FA↗

Cones of monotone functions generated by a generalized fractional maximal function

In this paper, we consider the generalized fractional maximal function and use it to introduce the space of generalized fractional maximal functions and the various cones of monotone functions generated by generalized fractional maximal functions $M_Φf$. We introduced three function classes. We give equivalent descriptions of such cones when the function $Φ$ belongs to some function classes. The conditions for their mutual covering are given. Then, these cones are used to construct a criterion for embedding the space of generalized fractional maximal functions into the rearrangement invariant spaces (RIS). The optimal RIS for such embedding is also described.

math.FA↗