We present in this paper a new method to determine the k largest singular values and their corresponding singular vectors for real rectangular matrices A ∈ Rn×m. Our approach is based on using a block version of the Power Method to compute an k-block SV D decomposition: Ak = UkΣkV T k , where Σk is a diagonal matrix with the k largest non-negative, monotonically decreasing diagonal σ1 ≥ σ2 · · ...

The speech enhancement techniques are often employed to improve the quality and intelligibility of the noisy speech signals. This paper discusses a novel technique for speech enhancement which is based on Singular Value Decomposition. This implementation utilizes a Genetic Algorithm based optimization method for reducing the effects of environmental noises from the singular vectors as well as t...

We extend the Golub-Kahan algorithm for computing the singular value decomposition of bidiagonal matrices to triangular matrices R. Our algorithm avoids the explicit formation of R T R or RRT. We derive a relation between left and right singular vectors of triangular matrices and use it to prove monotonic convergence of singular values and singular vectors. The convergence rate for singular val...

We propose a new seasonal adjustment method based on the regularized singular value decomposition (RSVD) of the matrix obtained by reshaping the seasonal time series data. The method is flexible enough to capture two kinds of seasonality: the fixed seasonality that does not change over time and the time-varying seasonality that varies from one season to another. RSVD represents the time-varying...

A new method of computation of singular values and left and right singular vectors of arbitrary nonsquare matrices has been proposed. The method permits to avoid solutions of high rank systems of linear equations of singular value decomposition problem, which makes it not sensitive to ill-conditioness of decomposed matrix. On base of Eckart-Young theorem, it was shown that each second order r-r...

Subsingular vectors of the N=2 superconformal algebras were discovered, and examples given, in 1996. Shortly afterwards Semikhatov and Tipunin claimed to have obtained a complete classification of the N=2 subsingular vectors in the paper ‘The Structure of Verma Modules over the N=2 Superconformal algebra’, hep-th/9704111, published in CMP 195 (1998) 129. Surprisingly, the only explicit examples...

The speech enhancement techniques are often employed to improve the quality and intelligibility of the noisy speech signals. This paper discusses a novel technique for speech enhancement which is based on Singular Value Decomposition. This implementation utilizes a Genetic Algorithm based optimization method for reducing the effects of environmental noises from the singular vectors as well as t...

This paper describes a computational method for improving the accuracy of a given singular value and its associated left and right singular vectors. The method is analogous to iterative improvement for the solution of linear systems. That is, by means of a low-precision computation, an iterative algorithm is applied to increase the accuracy of the singular value and vectors; extended precision ...

An alternative to singular value decomposition (SVD) in the information retrieval is the low-rank approximation of an original non-negative matrix A by its non-negative factors U and V . The columns of U are the feature vectors with no non-negative components, and the columns of V store the non-negative weights that serve for the combination of feature vectors. First experiments show that restr...