Erbay, Hasan2020-06-252020-06-252006closedAccess0096-30031873-5649https://doi.org/10.1016/j.amc.2005.04.072https://hdl.handle.net/20.500.12587/3621Erbay, Hasan/0000-0002-7555-541XThe truncated ULV decomposition (TULVD) provides good approximation to subspaces for the data matrix and can be modified quickly to reflect changes in the data. It also reveals the rank of the matrix. We develop an updating routine that is suitable for large scaled matrices of low rank. Numerical results presented that illustrate the accuracy of the algorithm. (c) 2005 Elsevier Inc. All rights reserved.eninfo:eu-repo/semantics/closedAccessmodifying decompositionssubspaces estimationArticle17321300130910.1016/j.amc.2005.04.0722-s2.0-32644439299Q1WOS:000236068400047Q2