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Journal ArticleDOI

Linear least squares solutions by householder transformations

Peter A. Businger, +1 more
- 01 Jun 1965 - 
- Vol. 7, Iss: 3, pp 269-276
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TLDR
In this paper, the euclidean norm is unitarily invariant and a vector x is determined such that x is parallel b-Ax parallel = \parallel c - QAx parallel where c denotes the first n components of c.
Abstract
Let A be a given m×n real matrix with m≧n and of rank n and b a given vector. We wish to determine a vector x such that $$\parallel b - A\hat x\parallel = \min .$$ where ∥ … ∥ indicates the euclidean norm. Since the euclidean norm is unitarily invariant $$\parallel b - Ax\parallel = \parallel c - QAx\parallel $$ where c=Q b and Q T Q = I. We choose Q so that $$QA = R = {\left( {_{\dddot 0}^{\tilde R}} \right)_{\} (m - n) \times n}}$$ (1) and R is an upper triangular matrix. Clearly, $$\hat x = {\tilde R^{ - 1}}\tilde c$$ where c denotes the first n components of c.

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Citations
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Journal ArticleDOI

Test procedures and test problems for least squares algorithms

TL;DR: Comparative results from running two types of problems on several different algorithms are given which illustrate some of the factors affecting computational accuracy: choice of algorithm, scaling of the data, tolerance parameters, and iterative refinement.
Proceedings ArticleDOI

Optimal redundancy resolution with task scaling under hard bounds in the robot joint space

TL;DR: This work presents an optimal differential kinematic inversion method in the presence of hard bounds on joint range, joint velocity, and joint acceleration, and recast the problem as a constrained quadratic programming (QP) problem, in which the joint velocity norm as well as the task scaling are to be minimized.
Journal ArticleDOI

Simple, direct and efficient multi-way spectral clustering

TL;DR: A new algorithm for spectral clustering based on a column-pivoted QR factorization that may be directly used for cluster assignment or to provide an initial guess for k-means, which is simple to implement, direct and requires no initial guess.
References
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Journal ArticleDOI

Unitary Triangularization of a Nonsymmetric Matrix

TL;DR: This note points out that the same result can be obtained with fewer arithmetic operations, and, in particular, for inverting a square matrix of order N, at most 2(N-1) square roots are required.