多尺度数据分析——信息融合与恒时聚类

Vistas in Astronomy Pub Date : 1997-01-01 DOI:10.1016/S0083-6656(97)00039-1

F. Murtagh , A. Aussem , J.-L. Starck

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引用次数: 1

摘要

我们描述了小波变换在多变量数据分析问题中的应用。在预测中，对时变数据进行多尺度变换可以对每个尺度进行预测，然后将各个预测结合起来。使用带噪声建模的小波变换进行点模式聚类，可能导致在恒定计算时间O(1)内聚类的结果，这一结果最初看起来是违反直觉的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multiscale data analysis - information fusion and constant-time clustering

We describe the use of the wavelet transform for multivariate data analysis problems. In prediction, a multiscale transform of time-varying data can allow forecasts of each scale, followed by a combining of the individual forecasts. The use of a wavelet transform with noise modeling for point pattern clustering can lead to the result, which initially appears counterintuitive, of clustering in constant computational time, O (1).

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