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The Application of Eigenvectors for the Construction of Minimum-Energy Wavelet Frames Based on FMRA

机译:特征向量在基于FMRA的最小能量小波框架构造中的应用

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摘要

In 1974, J. Morlet raised the concept of wavelet transform and established the inversion formula through the experience of physical intuition and signal processing. In 1986, Y. Meryer created a real small wave base, and the wavelet analysis began to flourish after a multi scale analysis of the same method of constructing the small wave base with S. Mallat. In order to analyze and deal with non-stationary signals, a series of new signal analysis theories are proposed.: Short Time Fourier Transform, time-frequency analysis, wavelet transform, and fractional Fourier transform and so on. In this paper, an explicit algorithm is given to construct the minimum-energy frames based on frame multiresolution analysis via characteristic vectors of the mask matrix. In section 2, we show the structure of minimum-energy wavelet frames in terms of their masks (Lemma 1) and discuss that we should eliminate the correlation of the rows of the mask matrix by the polyphase decomposition technique. Based on FMRA, an explicit algorithm is given to construct this frames. By this method, all the minimum-energy wavelet frames can be obtained. As an application, several examples are showed to explain this method in section 3. This method can also be applied in other fields of wavelet analysis.
机译:1974年,J。Morlet提出了小波变换的概念,并通过物理直觉和信号处理的经验建立了反演公式。 1986年,Y。Meryer创建了一个真正的小波基,在对与S. Mallat构造小波基的相同方法进行多尺度分析之后,小波分析开始蓬勃发展。为了分析和处理非平稳信号,提出了一系列新的信号分析理论:短时傅立叶变换,时频分析,小波变换和分数阶傅立叶变换等。本文提出了一种基于遮罩矩阵特征向量的基于帧多分辨率分析的最小能量帧构造算法。在第2节中,我们根据最小能量小波框架的掩码显示了结构(引理1),并讨论了应该通过多相分解技术消除掩码矩阵行的相关性。基于FMRA,给出了构造该帧的显式算法。通过这种方法,可以获得所有最小能量小波帧。作为应用,在第3节中显示了几个示例来说明此方法。该方法也可以应用于小波分析的其他领域。

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