Block Power Method for SVD Decomposition

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Block Power Method for SVD Decomposition

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 · · ...

متن کامل

A Numerical Method for Computing an SVD-like Decomposition

We present a numerical method to compute the SVD-like decomposition B = QDS−1, where Q is orthogonal, S is symplectic and D is a permuted diagonal matrix. The method can be applied directly to compute the canonical form of the Hamiltonian matrices of the form JBTB, where J = [ 0 −I I 0 ] . It can also be applied to solve the related application problems such as the gyroscopic systems and linear...

متن کامل

The Decomposition of DSP’s Control Logic Block for Power Reduction

The paper considers the architecture and low power design aspects of the digital signal processing block embedded into a three-phase integrated power meter IC. Utilized power reduction techniques were focused on the optimization of control logic block. The operations that control unit performs are described together with power optimization results.

متن کامل

Compare Adomian Decomposition Method and Laplace Decomposition Method for Burger's-Huxley and Burger's-Fisher equations

In this paper, Adomian decomposition method (ADM) and Laplace decomposition method (LDM) used to obtain series solutions of Burgers-Huxley and Burgers-Fisher Equations. In ADM the algorithm is illustrated by studying an initial value problem and LDM is based on the application of Laplace transform to nonlinear partial differential equations. In ADM only few terms of the expansion are required t...

متن کامل

Singular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD)

The singular value decomposition (SVD) is a generalization of the eigen-decomposition which can be used to analyze rectangular matrices (the eigen-decomposition is definedonly for squaredmatrices). By analogy with the eigen-decomposition, which decomposes a matrix into two simple matrices, the main idea of the SVD is to decompose a rectangular matrix into three simple matrices: Two orthogonal m...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Analele Universitatii "Ovidius" Constanta - Seria Matematica

سال: 2015

ISSN: 1844-0835

DOI: 10.1515/auom-2015-0024