Filter regularization for final value fractional diffusion problem with deterministic and random noise

In this paper, we consider an inverse problem for a time fractional diffusion equation with inhomogeneous source to determine the initial data from the observation data provided at a later time. In general, this problem is ill-posed, therefore we construct a regularized solution using the filter regularization method in both cases: the deterministic case and random noise case. First, we propose both parameter choice rule methods, the a-priori and the a-posteriori methods. Then, we obtain the convergence rates and provide examples of filters. We also provide a numerical example to illustrate our results.