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An investigation of time efficiency in wavelet-based markov parameter extraction methods

机译:基于小波的马尔可夫参数提取方法中时间效率的研究

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This paper investigates the time efficiency of using a wavelet transform-based method to extract the impulse response characteristics of a structural dynamic system. Traditional time domain procedures utilize the measured disturbances and response histories of a system to develop a set of auto and cross correlation functions. Through deconvolution of these functions, or matrix inversion, the Markov parameters of the system may be found, the size of the problem to be solved can be reduced as well as the computation time decreased. Fourier transforms are also used in this capacity as they may increase the time efficiency even more, but at the cost of accuracy. This paper will therefore compare the time requirements associated with a time, wavelet, and Fourier-based method of Markov parameter extraction, as well as their relative accuracy in modeling the system.`
机译:本文研究了基于小波变换的方法提取结构动力系统的脉冲响应特性的时间效率。传统的时域过程利用系统的测量干扰和响应历史来开发一组自动和互相关函数。通过这些函数的反卷积或矩阵求逆,可以找到系统的马尔可夫参数,可以减少要解决的问题的大小,并可以减少计算时间。傅里叶变换也用于此功能,因为它们可以进一步提高时间效率,但会降低准确性。因此,本文将比较与时间,小波和基于傅立叶的Markov参数提取方法相关的时间要求,以及它们在系统建模中的相对精度。

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