The Effectiveness of the Piecewise Monotonic Approximation Method for the Peak Estimation of Noisy Univariate Spectra

I. C. Demetriou, Ioannis N. Perdikas
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引用次数: 1

Abstract

We present examples of peak estimation to measurements of Raman, Infrared and NMR spectra by the piecewise monotonic data approximation method. The structural differences of these spectra, the complexity of the underlying physical laws and the error included in the measurements make this a good test of the effectiveness of the method. Precisely, if a number of monotonic sections of the data is required, then the optimal turning points and the least sum of squares of residuals are computed in quadratic complexity with respect to the number of data. This is a remarkable result because the problem may require an enormous number of combinations in order to find the optimal turning point positions. Our results exhibit some strengths and indicate certain advantages of the method. Therefore, they may be helpful to the development of new algorithms that are particularly suitable for peak estimation in spectroscopy calculations.
分段单调逼近法在有噪声单变量谱峰估计中的有效性
我们给出了用分段单调数据近似方法对拉曼光谱、红外光谱和核磁共振光谱测量进行峰估计的例子。这些光谱的结构差异、潜在物理定律的复杂性以及测量中包含的误差使该方法的有效性得到了很好的验证。准确地说,如果需要数据的许多单调部分,则以相对于数据数量的二次复杂度计算最佳拐点和最小残差平方和。这是一个显著的结果,因为这个问题可能需要大量的组合才能找到最佳的转折点位置。我们的结果显示出一些优势,并表明该方法具有一定的优势。因此,它们可能有助于开发特别适用于光谱计算中的峰值估计的新算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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