Name
Abstract | ||
|---|---|---|
This paper is concerned with an algorithm to compute the singular value decomposition (SVD) of time-varying square matrices. In a first step we consider the task of diagonalizing symmetric time-varying matrices A(t). A differential equation is proposed, whose solutions asymptotically track the diagonalizing transformation. In particular, perfect matching of the initial conditions is not required and the solutions converge exponentially towards the desired transformation. Then the desired differential equation for tracking the SVD is derived. Robustness of the algorithms is guaranteed by our approach. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/S0167-739X(02)00162-0 | Future Generation Comp. Syst. |
Keywords | Field | DocType |
singular value decomposition,diagonalizing transformation,differential equation,time-varying matrices,symmetric time-varying,solutions converge exponentially,perfect matching,time-varying matrix,square matrix,initial condition,continuation methods | Singular value decomposition,Applied mathematics,Differential equation,Mathematical optimization,Matrix (mathematics),Computer science,Singular solution,Square matrix,Matching (graph theory),Robustness (computer science),Exponential growth,Distributed computing | Journal |
Volume | Issue | ISSN |
19 | 3 | Future Generation Computer Systems |
Citations | PageRank | References |
7 | 0.72 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Markus Baumann | 1 | 11 | 1.96 |
| Uwe Helmke | 2 | 337 | 42.53 |