Efficient iterative solutions to complex-valued nonlinear least-squares problems with mixed linear and antilinear operators.

ABSTRACT: We consider a setting in which it is desired to find an optimal complex vector x ∈ C ^N that satisfies A (x) ≈ b in a least-squares sense, where b ∈ C ^M is a data vector (possibly noise-corrupted), and A (·) : C ^N → C ^M is a measurement operator. If A (·) were linear, this reduces to the classical linear least-squares problem, which has a well-known analytic solution as well as powerful iterative solution algorithms. However, instead of linear least-squares, this work considers the more complicated scenario where A (·) is nonlinear, but can be represented as the summation and/or composition of some operators that are linear and some operators that are antilinear. Some common nonlinear operati

SUBMITTER: Kim TH 

PROVIDER: S-EPMC9159680 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature