A HYBRID METHOD FOR REGULARIZED STRUCTURED LINEAR TOTAL LEAST NORM

A hybrid method solving regularized structured linear total least norm (RSTLN) problems, which have highly ill-conditioned coefficient matrix with special structures, is suggested and analyzed. This scheme combining RSTLN algorithm and separation by parts guarantees the convergence of parameters and has an advantages in reducing the residual norm and relative error of solutions. Computational tests for problems arisen in signal processing and image formation process confirm that the presenting method is effective for more accurate solutions to (R)STLN problem than the (R)STLN algorithm.