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Hutchinson metric : ウィキペディア英語版
Hutchinson metric

In mathematics, the Hutchinson metric is a function which measures "the discrepancy between two images for use in fractal image processing" and "can also be applied to describe the similarity between DNA sequences expressed as real or complex genomic signals."〔 (Efficient computation of the Hutchinson metric between digitized images ) abstract〕〔 (HUTCHINSON METRIC IN FRACTAL DNA ANALYSIS -- A NEURAL NETWORK APPROACH )〕
==Formal definition==
Consider only nonempty, compact, and finite metric spaces. For a space X \,, let P(X) \, denote the space of Borel probability measures on X \, , with
:\delta : X \rightarrow P(X) \,
the embedding associating to x \in X the point measure \delta_x \,. The support |\mu| \, of a measure in P(X) is the smallest closed subset of measure 1.
If
:f : X_1 \rightarrow X_2 \,
is Borel measurable then the induced map
:f_
* : P(X_1) \rightarrow P(X_2) \,
associates to \mu \, the measure f_
*(\mu) \, defined by
:f_
*(\mu)(B)= \mu(f^(B)) \,
for all B \, Borel in X_2 \, .
Then the Hutchinson metric is given by
:d(\mu_1,\mu_2)=\sup \left \lbrace \int u(x) \, \mu_1(dx) - \int u(x) \, \mu_2(dx) \right \rbrace
where the \sup is taken over all real-valued functions ''u'' with Lipschitz constant
\le 1 \,.
Then \delta \, is an isometric embedding of X \, into P(X) \, , and if
:f : X_1 \rightarrow X_2 \,
is Lipschitz then
:f_
* : P(X_1) \rightarrow P(X_2) \,
is Lipschitz with the same Lipschitz constant.〔 (Invariant Measures for Set-Valued Dynamical Systems Walter Miller; Ethan Akin Transactions of the American Mathematical Society, Vol. 351, No. 3. (Mar., 1999), pp. 1203-1225 ) 〕

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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