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A new wavelet family based on second-order LTI-systems

机译:基于二阶Lti-Systems的新小波家族

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In this paper, a new family of wavelets derived from the underdamped response of second-order Linear-Time-Invariant (LTI) systems is introduced. The most important criteria for a function or signal to be a wavelet is the ability to recover the original signal back from its continuous wavelet transform. We show that it is possible to recover back the original signal once the Second-Order Underdamped LTI (SOULTI) wavelet is applied to decompose the signal. It is found that the SOULTI wavelet transform of a signal satisfies a linear differential equation called the reconstructing differential equation, which is closely related to the differential equation that produces the wavelet. Moreover, a time-frequency resolution is defined based on two different approaches. The new transform has useful properties; a direct relation between the scale and the frequency, unique transform formulas that can be easily obtained for most elementary signals such as unit step, sinusoids, polynomials, and decaying harmonic signals, and linear relations between the wavelet transform of signals and the wavelet transform of their derivatives and integrals. The results obtained are presented with analytical and numerical examples. Signals with constant harmonics and signals with time-varying frequencies are analyzed, and their evolutionary spectrum is obtained. Contour mapping of the transform in the time-scale and the time-frequency domains clearly detects the change of the frequency content of the analyzed signals with respect to time. The results are compared with other wavelets results and with the short-time fourier analysis spectrograms. At the end, we propose the method of reverse wavelet transform to mitigate the edge effect.
机译:在本文中,引入了从二阶线性时不变(LTI)系统的被衰减响应的新的小波族。作为小波的功能或信号最重要的标准是能够从其连续小波变换恢复原始信号。我们表明,一旦施加二阶欠载LTI(Soulti)小波以分解信号,就可以恢复原始信号。发现信号的Soulti小波变换满足称为重建微分方程的线性微分方程,其与产生小波的微分方程密切相关。此外,基于两种不同的方法来定义时频分辨率。新变换有很有的属性;尺度与频率,独特的变换公式之间的直接关系,其可以容易地用于大多数基本信号,例如单元步骤,正弦波,多项式和衰减谐波信号,以及信号的小波变换与小波变换之间的线性关系他们的衍生物和积分。得到的结果具有分析和数值例子。分析具有恒定谐波的信号和具有时变频率的信号,并获得它们的进化谱。在时间尺度和时频域中的变换的轮廓映射清楚地检测到分析的信号的频率内容相对于时间的变化。将结果与其他小波效果和短时傅里叶分析谱图进行比较。最后,我们提出了反向小波变换的方法来减轻边缘效果。

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