Abstract
Calculating the variance of a family of tensors, each represented by a symmetric positive semi-definite second order tensor/matrix, involves the formation of a fourth order tensor Rabcd. To form this tensor, the tensor product of each second order tensor with itself is formed, and these products are then summed, giving the tensor Rabcd the same symmetry properties as the elasticity tensor in continuum mechanics. This tensor has been studied with respect to many properties: representations, invariants, decomposition, the equivalence problem et cetera. In this paper we focus on the two-dimensional case where we give a set of invariants which ensures equivalence of two such fourth order tensors Rabcd and . In terms of components, such an equivalence means that components Rijkl of the first tensor will transform into the components of the second tensor for some change of the coordinate system.
Highlights
Positive semi-definite second order tensors arise in several applications
In particular we study the equivalence problem, namely, we ask the question: given the components Ri jkl and Ri jkl of two such tensors do they represent the same tensor in different coordinate systems?
We started with a family of symmetric positivedefinite tensors in two dimensions and considered its variance
Summary
Positive semi-definite second order tensors arise in several applications. In image processing, a structure tensor is computed from greyscale images that captures the local orientation of the image intensity variations [10, 17] and is employed to address a broad range of challenges. Diffusion tensor magnetic resonance imaging (DT-MRI) [1, 5] characterizes anisotropic water diffusion by enabling the measurement of the apparent diffusion tensor, which makes it possible to delineate the fibrous structure of the tissue. Recent work has shown that diffusion MR measurements of
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