Fifth Property of the Euclidean Metric

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(→Fifth property of the Euclidean metric '''('''relative-angle inequality''')''')
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Augmenting the four fundamental Euclidean metric properties in <math>\mathbb{R}^n</math>,
Augmenting the four fundamental Euclidean metric properties in <math>\mathbb{R}^n</math>,
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for all <math>i_{},j_{},\ell\neq k_{}\!\in\!\{1\ldots_{}N\}</math> ,
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&nbsp;for all &nbsp;<math>i_{},j_{},\ell\neq k_{}\!\in\!\{1\ldots_{}N\}</math> ,
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<math>i\!<\!j\!<\!\ell</math> , and for <math>N\!\geq_{\!}4</math> distinct points <math>\{x_k\}</math> ,
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&nbsp;<math>i\!<\!j\!<\!\ell</math> , &nbsp;and for &nbsp;<math>N\!\geq_{\!}4</math>&nbsp; distinct points &nbsp;<math>\{x_k\}</math> , &nbsp;the inequalities
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the inequalities
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<math>\begin{array}{cc}
<math>\begin{array}{cc}
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\end{array}</math>
\end{array}</math>
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where <math>\theta_{ikj}\!=_{}\!\theta_{jki}</math> is the angle between vectors at vertex <math>x_k</math> , must be satisfied at each point <math>x_k</math> regardless of affine dimension.
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where &nbsp;<math>\theta_{ikj}\!=_{}\!\theta_{jki}</math>&nbsp; is the angle between vectors at vertex &nbsp;<math>x_k</math> &nbsp;, &nbsp;&nbsp;must be satisfied at each point &nbsp;<math>x_k</math>&nbsp; regardless of affine dimension.
== References ==
== References ==
* Dattorro, [http://www.convexoptimization.com Convex Optimization & Euclidean Distance Geometry], Meboo, 2007
* Dattorro, [http://www.convexoptimization.com Convex Optimization & Euclidean Distance Geometry], Meboo, 2007

Revision as of 01:17, 31 October 2007

For a list of points LaTeX: \{x_\ell\in\mathbb{R}^n,\,\ell\!=\!1\ldots N\} in Euclidean vector space, distance-square between points LaTeX: x_i and LaTeX: x_j is defined

LaTeX: \begin{array}{rl}d_{ij} \!\!&=\,\|x_i-_{}x_j\|^2 ~=~(x_i-_{}x_j)^T(x_i-_{}x_j)~=~\|x_i\|^2+\|x_j\|^2-2_{}x^T_i\!x_j\\\\ &=\,\left[x_i^T\quad x_j^T\right]\left[\begin{array}{*{20}r}\!I&-I\\\!-I&I\end{array}\right] \left[\!\!\begin{array}{*{20}c}x_i\\x_j\end{array}\!\!\right] \end{array}

Euclidean distance between points must satisfy the defining requirements imposed upon any metric space: [Dattorro, ch.5.2]

namely, for Euclidean metric LaTeX: \sqrt{d_{ij}} in LaTeX: \mathbb{R}^n

  • LaTeX: \sqrt{d_{ij}}\geq0\,,~~i\neq j                                       (nonnegativity)
  • LaTeX: \sqrt{d_{ij}}=0\,,~~i=j                                       (self-distance)
  • LaTeX: \sqrt{d_{ij}}=\sqrt{d_{ji}}                                                  (symmetry)
  • LaTeX: \sqrt{d_{ij}}\,\leq\,\sqrt{d_{ik_{}}}+\sqrt{d_{kj}}~,~~i\!\neq\!j\!\neq\!k    (triangle inequality)


Fifth property of the Euclidean metric (relative-angle inequality)

Augmenting the four fundamental Euclidean metric properties in LaTeX: \mathbb{R}^n,  for all  LaTeX: i_{},j_{},\ell\neq k_{}\!\in\!\{1\ldots_{}N\} ,  LaTeX: i\!<\!j\!<\!\ell ,  and for  LaTeX: N\!\geq_{\!}4  distinct points  LaTeX: \{x_k\} ,  the inequalities

LaTeX: \begin{array}{cc} |\theta_{ik\ell}-\theta_{\ell kj}|~\leq~\theta_{ikj\!}~\leq~\theta_{ik\ell}+\theta_{\ell kj}\\ \theta_{ik\ell}+\theta_{\ell kj}+\theta_{ikj\!}\,\leq\,2\pi\\ 0\leq\theta_{ik\ell\,},\theta_{\ell kj\,},\theta_{ikj}\leq\pi \end{array}

where  LaTeX: \theta_{ikj}\!=_{}\!\theta_{jki}  is the angle between vectors at vertex  LaTeX: x_k  ,   must be satisfied at each point  LaTeX: x_k  regardless of affine dimension.

References

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