Newton-like methods for numerical optimization on manifolds
Many problems in signal processing require the numerical optimization of a cost function which is defined on a smooth manifold. Especially, orthogonally or unitarily constrained optimization problems tend to occur in signal processing tasks involving subspaces. In this paper we consider Newton-like methods for solving these types of problems. Under the assumption that the parameterization of the manifold is linked to so-called Riemannian normal coordinates our algorithms can be considered as...[Show more]
|Collections||ANU Research Publications|
|Source:||Thirty-Eighth Asilomar Conference on Signals, Systems and Computers|
|01_Hueper_Newton-like_methods_for_2004.pdf||548.67 kB||Adobe PDF||Request a copy|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.