A new pitch estimation method for song sounds using twelve comb filters and singular value decomposition (SVD) processing is presented. This method is based on the ability of a comb filter, corresponding to one tone, to eliminate the tone’s pitch and harmonic frequencies, and also on the relationship between the number of singular values obtained from the SVD and the number of the signal freque...

We propose new algorithms for singular value decomposition (SVD) of very large-scale matrices based on a low-rank tensor approximation technique called the tensor train (TT) format. The proposed algorithms can compute several dominant singular values and corresponding singular vectors for large-scale structured matrices given in a TT format. The computational complexity of the proposed methods ...

Abstract This paper presents a robust watermarking for still digital images based on schur factorization and Singular Value Decomposition (SVD). In this paper, image is decomposed into 8 8  blocks and after applying schur factorization, the stable largest eigen values of the upper triangle is used as robust locations for embedding watermark. The matrix array formed by largest eigen values furt...

The *congruence class of a least square solution for the following matrix equations AX = B, AXA = D, AXB = D and (AX XB) = (E F) is presented. Also, we derive necessary and sufficient conditions for the existence of a least square solution and present a general form of such solutions using the Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD). Crown Copyrigh...

We propose a novel scheme for watermarking of digital images based on singular value decomposition (SVD), which makes use of the fact that the SVD subspace preserves significant amount of information of an image, as compared to its singular value matrix, Zhang and Li (2005). The principal components of the watermark are embedded in the original image, leaving the detector with a complimentary s...

In this paper, we develop a new image quality assessment scheme with the use of Singular Value Decomposition (SVD). In a previous work [1], only the singular values out of SVD were used for quality assessment. We show that singular vectors are even more important than singular values for quality assessment. Hence, we use both singular vectors and values for comprehensive image quality evaluatio...

The main objective of this paper is to expound the singular-value-decomposition (SVD)-based reduction technique proposed to single-input–single-output Takagi-Sugeno (TS) fuzzy models to multivariable cases. The use of higher order singular value decomposition is proposed in this paper for the complexity reduction of multiple-input–single-output TS fuzzy model approximation. A detailed illustrat...