著者

Jeff Irion Naoki Saito

出版者

一般社団法人 日本応用数理学会

雑誌

JSIAM Letters (ISSN:18830609)

巻号頁・発行日

vol.6, pp.21-24, 2014 (Released:2014-05-16)

参考文献数

16

被引用文献数

19

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We describe a new transform that generates a dictionary of bases for handling data on a graph by combining recursive partitioning of the graph and the Laplacian eigenvectors of each subgraph. Similar to the wavelet packet and local cosine dictionaries for regularly sampled signals, this dictionary of bases on the graph allows one to select an orthonormal basis that is most suitable to one's task at hand using a best-basis type algorithm. We also describe a few related transforms including a version of the Haar wavelet transform on a graph, each of which may be useful in its own right.