English

A Centroid for Sections of a Cube in a Function Space, with application to Colorimetry

Functional Analysis 2020-03-16 v4

Abstract

The definition of the centroid in finite dimensions does not apply in a function space because of the lack of a translation invariant measure. Another approach, suggested by Nik Weaver, is to use a suitable collection of finite-dimensional subspaces. For a specific collection of subspaces of L1[0,1]L^1[0,1], this approach is shown to be successful when the subset is the intersection of a cube with a closed affine subspace of finite codimension. The techniques used are the classical Laplace Transform and saddlepoint method for asymptotics. Applications to spectral reflectance estimation in colorimetry are presented.

Keywords

Cite

@article{arxiv.1811.00990,
  title  = {A Centroid for Sections of a Cube in a Function Space, with application to Colorimetry},
  author = {Glenn Davis},
  journal= {arXiv preprint arXiv:1811.00990},
  year   = {2020}
}

Comments

41 pages, 10 figures. In v2 revised argument in section 5; the new argument uses the Jordan-Brouwer separation theorem, instead of a global diffeomorphism theorem of Hadamard. In v3 section 5, added two variants of a key lemma. In v4 added remarks about the Langevin function, and more references

R2 v1 2026-06-23T05:02:27.684Z