Regularized solution approximation of a fractional pseudo-parabolic problem with a nonlinear source term and random data

Nguyen Huu Can, Yong Zhou, Nguyen Huy Tuan and Tran Ngoc Thach

Chaos, Solitons & Fractals, 2020, vol. 136, issue C

Abstract: In this paper, we consider a multi-dimensional fractional pseudo-parabolic problem with nonlinear source in case the input data is measured on a discrete set of points instead of the whole domain. For any number of dimensions, the solution is not stable. This makes the problem we are interested in be ill-posed. Here, we construct regularized solutions for this problem in two cases of number of dimensions (denoted by m) including m=2 and m is arbitrary. In each case, we show the uniqueness of the regularized solution and give the error estimates. Finally, the convergence rate is also investigated numerically.

Keywords: Inverse problem; Pseudo-parabolic equation; Regularized solution; Discrete data (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:136:y:2020:i:c:s0960077920302472

DOI: 10.1016/j.chaos.2020.109847

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