Nonnegative tensor partition

来源 :2016年张量和矩阵学术研讨会(International conference on Tensor, Matrix a | 被引量 : 0次 | 上传用户:a596298067
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
  In this talk, we discuss the partition of a nonnegative tensor which is intended for finding its spectral radius via the spectral radii of its principal blocks. Based on which, we can establish a necessary and sufficient condition for a nonnegative tensor having a positive eigenvector.
其他文献
  We study the nonlinear Schr(o)dinger systems which consist of three equations with variational structure. The functional for our systems has three coupling
会议
  In this talk we consider an elliptic problem under overdetermined boundary conditions: the solution vanishes at the boundary and the normal derivative is co
会议
  In Quantum Chemistry, an important class of models involve a system of coupled nonlinear eigenvalue problems which are the Euler-Lagrange equations of an en
会议
  Let Ω(() RN be a bounded regular domain of dimension N ≥ 1, h a positive L1 function on Ω. Elliptic equations of singular growth like -△u = h(x)/ up in
会议
  A Z-matrix is a real square matrix with non-positive off- diagonal entries. Con-sidering its generalization to Z-transformations on proper cones and Z-tenso
会议
  We will talk about some latest research results on · semi-classical solutions of nonlinear Dirac equations; · bifurcation on compact spin manifolds; · co
会议
  Let m, m, n be positive integers. Let A be an mth order n-dimensional complex tensor and B be an m0th order n-dimensional complex tensor. Suppose that Bxm i
会议
  Two major tools in the study of multi-relational datasets are (i) higher-order Markov chains and (ii) linear algebra-inspired computations on hypermatrices
会议
  It is known that computing the largest(smallest) Z-eigenvalue of a symmetric ten-sor is equivalent to maximizing(minimizing) a homogeneous polynomial over t
会议
  The nonnegative tensor (matrix) factorization finds more and more applications in various disciplines including machine learning, data mining, and blind sou
会议