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HOSVD-wavelet based framework for multidimensional data approximation

机译:基于HOSVD小波的多维数据近似框架

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摘要

The representation of data plays significant role in many applications, as for instance when performing data compression, feature extraction or enhancement, etc. In this paper we briefly mention some well known data representation forms and propose a new domain based on the so called higher order singular value decomposition (HOSVD) and wavelet transformation. It will be shown how the data can be processed by manipulating its components in this domain. Furthermore, the properties of the components as well as the applicability of the proposed approach in the field of image processing and system identification will be shown.
机译:数据的表示在许多应用程序中起着重要的作用,例如在执行数据压缩,特征提取或增强等时。在本文中,我们简要介绍了一些众所周知的数据表示形式,并基于所谓的高阶提出了一个新领域。奇异值分解(HOSVD)和小波变换。将显示如何通过在此域中操纵其组件来处理数据。此外,将显示组件的属性以及所提出的方法在图像处理和系统识别领域中的适用性。

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