Bunch JR, Nielsen CP (1978) Updating the singular value decomposition. Numer Math 31:111-120Updating the Singular Value Decomposition - Bunch, Nielsen () Citation Context ...e for the classification of the queries. The subspace learning with the dimensional increment of the feature space can be...
Let A be an m×n matrix with known singular value decomposition. The computation of the singular value decomposition of a matrix is considered, where is obtained by appending a row or a column to A when m ≧ n or by deleting a row or a column from A when m > n . An algorithm is...
This paper discusses a few algorithms for updating the approximate Singular Value Decomposition (SVD) in the context of information retrieval by Latent Semantic Indexing (LSI) methods. A unifying framework is considered which is based on Rayleigh-Ritz projection methods. First, a Rayleigh-Ritz approac...
The analysis of symmetric saddle point systems with augmented Lagrangian method using Generalized Singular Value Decomposition (GSVD) has been carried out by Dluzewska [34]. The null-space approach was suggested by Scott and Tuma to solve large-scale saddle point problems involving small and non-...
Recently, Titurus and Friswell =-=[11]-=- presented the sensitivity-based model-updating method with an additional regularization criterion and computed the solutions based on the generalized singular value decomposition. Specific features o...
As often required in practice and theory, we aim to forecast the accumulated booking curve as well as the number of expected reservations for each day in the booking horizon. To reduce the high dimensionality of this problem, we apply singular value decomposition on the historical booking ...
Jacobi-type singular value decomposition (SVD) is an exceptionally suitable method for recursive SVD updating. It has a low computational complexity per up... A Kavcic,B Yang 被引量: 5发表: 1995年 A CORDIC Processor Array for the SVD of a Complex Matrix Matrix factorizations are important in...
This paper describes the results obtained from the merg-ing of two techniques that provide improvements to search and retrieval using Latent Semantic Indexing (LSI): Essen-tial Dimensions of LSI (EDLSI) and partial singular value decomposition (PSVD) updating. EDLSI utilizes an imple-mentation of...
In the first rule, a singular value decomposition of matrix S is performed to obtain k singular values, i.e. σ1 > σ2 > ... > σk > 0. Based on the principle of singular value dichotomy [29], the appropriate regularization parameter ξ is then chosen among these singular values(22...
The quotient singular value decomposition of two matrices, A and B, with an equal number of rows m, has been described in several ways. The justification for the name is most obvious when A and B are both square and of the same size and when B has full rank. Suppose an application ...