The goal of this thesis is to understand the deviatoric decomposition of tensors of higher order in 2 and 3 dimensions. In the first chapter an introduction to tensor algebra will be given. Chapter 2 and 3 concentrate on establishing a recursive formula for the deviatoric decomposition in 2D and 3D, respectively. This recursive formula is the key to prove by induction the existense of a deviatoric decomposition for any tensor. Useful examples will also be given at the end of each chapter.:Introduction 1. Introduction to Tensor Algebra 2. Orthogonal Irreducible Decomposition for 2D Tensors 3. Orthogonal Irreducible Decomposition for 3D Tensors 4. Conclusion Bibliography 5. Declaration of Originalit
The direct sum decomposition of tensor products for SU(3) has many applications in physics, and the ...
Canonical polyadic decomposition (CPD) of a third-order tensor is decomposition in a minimal number ...
Abstract. This survey provides an overview of higher-order tensor decompositions, their applications...
The goal of this thesis is to understand the deviatoric decomposition of tensors of higher order in ...
\u3cp\u3eWhile every matrix admits a singular value decomposition, in which the terms are pairwise o...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
AbstractOperations with tensors, or multiway arrays, have become increasingly prevalent in recent ye...
Canonical polyadic decomposition (CPD) of a higher-order tensor is decomposition into a minimal numb...
The direct sum decomposition of tensor products for SU(3) has many applications in physics, and the ...
Tensors are combinations of several vectors such that a bigger vector space, also calledthe tensor s...
The direct sum decomposition of tensor products for SU(3) has many applications in physics, and the ...
Canonical polyadic decomposition (CPD) of a third-order tensor is decomposition in a minimal number ...
Abstract. This survey provides an overview of higher-order tensor decompositions, their applications...
The goal of this thesis is to understand the deviatoric decomposition of tensors of higher order in ...
\u3cp\u3eWhile every matrix admits a singular value decomposition, in which the terms are pairwise o...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal...
AbstractOperations with tensors, or multiway arrays, have become increasingly prevalent in recent ye...
Canonical polyadic decomposition (CPD) of a higher-order tensor is decomposition into a minimal numb...
The direct sum decomposition of tensor products for SU(3) has many applications in physics, and the ...
Tensors are combinations of several vectors such that a bigger vector space, also calledthe tensor s...
The direct sum decomposition of tensor products for SU(3) has many applications in physics, and the ...
Canonical polyadic decomposition (CPD) of a third-order tensor is decomposition in a minimal number ...
Abstract. This survey provides an overview of higher-order tensor decompositions, their applications...