NORM MINIMIZATION ON NONLINEAR MANIFOLDS IN HILBERT SPACE,

Abstract

A problem in estimation theory that frequently arises in aerospace technology is the determination of a 'best estimate' of a set of parameters x given a sequence of noisy measurements y sub 1, y sub 2,...,y sub n and the fact that, in the absence of noise, a nonlinear equation of the form f(x,y sub i) = 0 is satisfied. The solution to this nonlinear estimation problem is dependent upon finding a computational method for minimizing norm z subject to a nonlinear constraint g(z) = 0. This paper considers the problem of minimizing norm z on the manifold M = (z: g(z) = 0), where g is a suitably differentiable function mapping the Hilbert space E into the Hilbert space F. A method is given for generating a sequence of points (in braces: z sub k) in E such that g(z sub k) converges to zero and which, under suitable additional assumptions, converges to an element in M of minimum norm. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1968
Accession Number
AD0678976

Entities

People

  • Frederick C. Johnson

Organizations

  • Boeing

Tags

DTIC Thesaurus Topics

  • Computational Science
  • Equations
  • Hilbert Space
  • Mathematics
  • Measurement
  • Sequences

Readers

  • Approximation Theory.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Calculus or Mathematical Analysis

Technology Areas

  • Space