Matrix inversion cases with size-independent tensor rank estimates

نویسندگان
چکیده

برای دانلود رایگان 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

Toward automated directivity estimates in earthquake moment tensor inversion

Hsin-Hua Huang,1,2,3 Naofumi Aso2,4 and Victor C. Tsai2 1Institute of Earth Science, Academia Sinica, Taipei 115, Taiwan. E-mail: [email protected] 2Seismological Laboratory, California Institute of Technology, Pasadena, CA 91125, USA 3Department of Geology and Geophysics, University of Utah, Salt Lake City, UT 84112, USA 4Department of Earth and Planetary Science, The University of T...

متن کامل

​Rank based Least-squares Independent Component Analysis

  In this paper, we propose a nonparametric rank-based alternative to the least-squares independent component analysis algorithm developed. The basic idea is to estimate the squared-loss mutual information, which used as the objective function of the algorithm, based on its copula density version. Therefore, no marginal densities have to be estimated. We provide empirical evaluation of th...

متن کامل

Algorithms for Independent Low-Rank Matrix Analysis

This document summarizes an algorithm for independent low-rank matrix analysis, which was proposed as determined rank-1 multichannel nonnegative matrix factorization in the following published papers: Daichi Kitamura, Nobutaka Ono, Hiroshi Sawada, Hirokazu Kameoka, and Hiroshi Saruwatari, “Efficient multichannel nonnegative matrix factorization exploiting rank-1 spatial model,” Proceedings of I...

متن کامل

Factor Matrix Nuclear Norm Minimization for Low-Rank Tensor Completion

Most existing low-n-rank minimization algorithms for tensor completion suffer from high computational cost due to involving multiple singular value decompositions (SVDs) at each iteration. To address this issue, we propose a novel factor matrix rank minimization method for tensor completion problems. Based on the CANDECOMP/PARAFAC (CP) decomposition, we first formulate a factor matrix rank mini...

متن کامل

Matrix Generation in Isogeometric Analysis by Low Rank Tensor Approximation

It has been observed that the task of matrix assembly in Isogeometric Analysis (IGA) is more challenging than in the case of traditional finite element methods. The additional difficulties associated with IGA are caused by the increased degree and the larger supports of the functions that occur in the integrals defining the matrix elements. Recently we introduced an interpolation-based approach...

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: Linear Algebra and its Applications

سال: 2009

ISSN: 0024-3795

DOI: 10.1016/j.laa.2009.03.001