Results 21 to 30 of about 2,893,048 (303)
The Tensor Product of Polynomials [PDF]
Experimental Mathematics, 1999 Using Grobner basis algorithms in MAGMA we find necessary and sufficient conditions for a polynomial of degree 6 over any field to bethe tensor product of two polynomials, one of degree 3 and one of degree 2.
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On the convergence of the combination technique [PDF]
, 2013 Sparse tensor product spaces provide an efficient tool todiscretize higher dimensional operator equations. The direct Galerkin method in such ansatz spaces may employ hierarchical bases, interpolets, wavelets or multilevel frames. Besides, an alternative
Griebel, Michael +5 more
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WOVEN FRAMES IN TENSOR PRODUCT OF HILBERT SPACES [PDF]
Journal of Algebraic Systems, 2020 The tensor product is the fundemental ingredient for extending one-dimensional techniques of filtering and compression in signal preprocessing to higher dimensions.
S. Afshar Jahanshahi, A. Ahmadi
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Stabilizing tensor products [PDF]
Proceedings of the American Mathematical Society, 1975 Let C C be a symmetric monoidal category with a suspension, and let SC be the ...
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TENSOR PRODUCT OF INCIDENCE ALGEBRAS [PDF]
, 2015 The aim of this work is to study the incidence functions and the tensor product of two incidence algebras. We show that the tensor product of two incidence algebras is an incidence algebra.
Alghamdi, Ahmad, Ahmad Alghamdi
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IEEE Transactions on Quantum Engineering, 2020 We provide a procedure to construct entanglement-assisted Calderbank-Shor-Steane (CSS) codes over qudits from the parity check matrices of two classical codes over Fq, where q = pk, p is prime, and k is a positive integer.
Priya J. Nadkarni +1 more
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Localizations of tensor products
Rendiconti del Seminario Matematico della Università di Padova, 2014 A homomorphism {\lambda}:A\rightarrow B between R -modules is called a localization if for all {\varphi} \in Hom_{R}(A,B)
Dugas, Manfred +2 more
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Tensor-matrix products with a compressed sparse tensor [PDF]
Proceedings of the 5th Workshop on Irregular Applications: Architectures and Algorithms, 2015 The Canonical Polyadic Decomposition (CPD) of tensors is a powerful tool for analyzing multi-way data and is used extensively to analyze very large and extremely sparse datasets. The bottleneck of computing the CPD is multiplying a sparse tensor by several dense matrices. Algorithms for tensor-matrix products fall into two classes.
Shaden Smith, George Karypis
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Journal of Pure and Applied Algebra, 2009 Let \(A=A_1\oplus\cdots\oplus A_r\) be a decomposition of the associative algebra \(A\) as a direct sum of its vector subspaces \(A_i\). This decomposition is regular if for any choice of the indices \(i_j\) one has \(A_{i_1}\cdots A_{i_n}\neq 0\), and furthermore for every \(i\) and \(j\) and every \(x_i\in A_i\), \(x_j\in A_j\) one has \(x_ix_j ...
Bahturin, Yuri, Regev, Amitai
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Tensor product semigroups on locally convex spaces [PDF]
, 2021 In this paper, we introduce tensor product semigroups of operators on locally convex spaces. The basic properties are presented. We give multiple relations between the tensor product semigroups and its components.
El Beldi, Mouad +3 more
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