Geometric diffusions as a tool for harmonic analysis and structure definition of data: Multiscale methods

被引:139
作者
Coifman, RR
Lafon, S
Lee, AB
Maggioni, M
Nadler, B
Warner, F
Zucker, SW
机构
[1] Yale Univ, Dept Mat, Program Appl Math, New Haven, CT 06510 USA
[2] Yale Univ, Dept Comp Sci, New Haven, CT 06510 USA
关键词
D O I
10.1073/pnas.0500896102
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In the companion article, a framework for structural multiscale geometric organization of subsets of R-n and of graphs was introduced. Here, diffusion semigroups are used to generate multiscale analyses in order to organize and represent complex structures. We emphasize the multiscale nature of these problems and build scaling functions of Markov matrices (describing local transitions) that lead to macroscopic descriptions at different scales. The process of iterating or diffusing the Markov matrix is seen as a generalization of some aspects of the Newtonian paradigm, in which local infinitesimal transitions of a system lead to global macroscopic descriptions by integration. This article deals with the construction of fast-order N algorithms for data representation and for homogenization of heterogeneous structures.
引用
收藏
页码:7432 / 7437
页数:6
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