Wichita State University
We present a novel parameter choice strategy for the conjugate gradient algorithm viewed as a regularization tool for the solution of least squares problems and associated normal equations. Our approach relies on the Lanczos bidiagonalization process and does not assume a priori information about the magnitude of the measurement error. We compare our method with one proposed by Hanke and Raus and illustrate its performance with numerical experiments, including an inverse problem of acoustic source detection. This is joint work with Thomas DeLillo.
Please join us for refreshments before the lecture at 2:30p.m. in room 353 Jabara Hall.
[ Fall 2001]