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Asymptotic order of the quantization errors for a class of self-affine measures
Author(s) -
Sanguo Zhu
Publication year - 2017
Publication title -
proceedings of the american mathematical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.968
H-Index - 84
eISSN - 1088-6826
pISSN - 0002-9939
DOI - 10.1090/proc/13756
Subject(s) - algorithm , artificial intelligence , computer science
Let E E be a Bedford-McMullen carpet determined by a set of affine mappings ( f i j ) ( i , j ) ∈ G (f_{ij})_{(i,j)\in G} and μ \mu a self-affine measure on E E associated with a probability vector ( p i j ) ( i , j ) ∈ G (p_{ij})_{(i,j)\in G} . We prove that, for every r ∈ ( 0 , ∞ ) r\in (0,\infty ) , the upper and lower quantization coefficient are always positive and finite in its exact quantization dimension s r s_r . As a consequence, the n n th quantization error for μ \mu of order r r is of the same order as n − 1 s r n^{-\frac {1}{s_r}} . In sharp contrast to the Hausdorff measure for Bedford-McMullen carpets, our result is independent of the horizontal fibres of the carpets.

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