General tensor decomposition, moment matrices and applications
نویسندگان
چکیده
The tensor decomposition addressed in this paper may be seen as a generalisation of Singular Value Decomposition of matrices. We consider general multilinear and multihomogeneous tensors. We show how to reduce the problem to a truncated moment matrix problem and give a new criterion for flat extension of Quasi-Hankel matrices. We connect this criterion to the commutation characterisation of border bases. A new algorithm is described. It applies for general multihomogeneous tensors, extending the approach of J.J. Sylvester to binary forms. An example illustrates the algebraic operations involved in this approach and how the decomposition can be recovered from eigenvector computation.
منابع مشابه
Tensor Networks for Latent Variable Analysis. Part I: Algorithms for Tensor Train Decomposition
Decompositions of tensors into factor matrices, which interact through a core tensor, have found numerous applications in signal processing and machine learning. A more general tensor model which represents data as an ordered network of sub-tensors of order-2 or order-3 has, so far, not been widely considered in these fields, although this so-called tensor network decomposition has been long st...
متن کاملAn Algebraic Solution for the Candecomp/PARAFAC Decomposition with Circulant Factors
The Candecomp/PARAFAC decomposition (CPD) is an important mathematical tool used in several fields of application. Yet, its computation is usually performed with iterative methods which are subject to reaching local minima and to exhibiting slow convergence. In some practical contexts, the data tensors of interest admit decompositions constituted by matrix factors with particular structure. Oft...
متن کاملParametrization of general seismic potency and moment tensors for source inversion of seismic waveform data
S U M M A R Y We decompose a general seismic potency tensor into isotropic tensor, double-couple tensor and compensated linear vector dipole using the eigenvectors and eigenvalues of the full tensor. Two dimensionless parameters are used to quantify the size of the isotropic and compensated linear vector dipole components. The parameters have well-defined finite ranges and are suited for non-li...
متن کاملA constructive arbitrary-degree Kronecker product decomposition of matrices
We propose a constructive algorithm, called the tensor-based Kronecker product (KP) singular value decomposition (TKPSVD), that decomposes an arbitrary real matrix A into a finite sum of KP terms with an arbitrary number of d factors, namely A = ∑R j=1 σj A dj ⊗ · · · ⊗A1j . The algorithm relies on reshaping and permuting the original matrix into a d-way tensor, after which its tensor-train ran...
متن کاملContraction and decomposition matrices for vacuum diagrams
Tensor reduction of vacuum diagrams uses contraction and decomposition matrices. We present general recurrence relations for the calculation of those matrices and an explicit formula for the 3-loop decomposition matrix and its determinant. Email: Kenny [email protected] Email: [email protected] 1
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Symb. Comput.
دوره 52 شماره
صفحات -
تاریخ انتشار 2013