Regularization of an inverse source problem for fractional diffusion-wave equations under a general noise assumption

We consider the ill-posed inverse problem of determining an unknown source term appearing in abstract fractional diffusion-wave equations from a general noise assumption. Based on a H & ouml;lder-type source condition, we give the theoretical order optimality as well as the conditional stability result. To solve the problem, we propose fractional filter regularization methods, which can be regarded as an extension of the classical Tikhonov and Landweber methods. The idea is first to transform the problem into an ill-posed operator equation, then construct the regularization methods for the operator equation by introducing a suitable fractional filter function. As a natural further step, we study the convergence of the regularization methods, for which we derive order optimal rates of convergence under both a priori and a posteriori parameter choice rules. Applications of our fractional filter functions to both the fractional Tikhonov and the fractional Landweber filters are also investigated. Finally, three numerical examples in one-dimensional and two-dimensional cases are tested to validate our theoretical results.