在输出信号对输入信号的表示方面超越自适应 LMS 滤波器的质子方法变体

Parthasarathy Srinivasan
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引用次数: 0

摘要

普罗尼在其 1795 年的开创性论文中提出了用于逼近包含正弦/指数成分信号的普罗尼方法。然而,普罗尼方法只是在计算时代到来后才在现实世界中得到应用,计算时代的到来使得该方法本身所要求的大量复杂数值计算和劳动变得可行。自 1965 年诞生以来,自适应 LMS 滤波法一直是信号滤波和近似的最常用方法,但它并不能始终如一地提供高精度的结果,本研究的扩展实验也证明了这一点。作为一种补救措施,本研究对普罗尼方法进行了改进,发现在普罗尼计算本身的初始步骤中,可以对自回归模型设置中的计算误差进行调整,在此前提下可以获得更好(更精确)的计算近似结果。这种调整与同一自回归模型中系数的偏差成正比。与使用自适应 LMS 滤波器获得的结果相比,这一改进所获得的结果达到了预期目标,即获得一致性和更高精度的输出(恢复信号)近似值。
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A prony method variant which surpasses the Adaptive LMS filter in the output signal's representation of input
The Prony method for approximating signals comprising sinusoidal/exponential components is known through the pioneering work of Prony in his seminal dissertation in the year 1795. However, the Prony method saw the light of real world application only upon the advent of the computational era, which made feasible the extensive numerical intricacies and labor which the method demands inherently. The Adaptive LMS Filter which has been the most pervasive method for signal filtration and approximation since its inception in 1965 does not provide a consistently assured level of highly precise results as the extended experiment in this work proves. As a remedy this study improvises upon the Prony method by observing that a better (more precise) computational approximation can be obtained under the premise that adjustment can be made for computational error , in the autoregressive model setup in the initial step of the Prony computation itself. This adjustment is in proportion to the deviation of the coefficients in the same autoregressive model. The results obtained by this improvisation live up to the expectations of obtaining consistency and higher value in the precision of the output (recovered signal) approximations as shown in this current work and as compared with the results obtained using the Adaptive LMS Filter.
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