A Discrepancy Principle for Tikhonov Regularization with Approximately Specified Data

Many discrepancy principles are known for choosing the parameter in the regularized operator equation (T T + I)x = T y , ky ?y k , in order to approximate the minimal norm least-squares solution of the operator equation Tx = y. In this paper we consider a class of discrepancy principles for choosing the regularization parameter when T T and T y are approximated by A n and z n respectively with A n not necessarily self{adjoint. This procedure generalizes the work of Engl and Neubauer (1985), and particular cases of the results are applicable to the regularized projection method as well as to a degenerate kernel method considered by Groetsch (1990).