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A Fast, Accurate, and Separable Method for Fitting a Gaussian Function [Tips & Tricks]
IEEE Signal Processing Magazine ( IF 9.4 ) Pub Date : 2019-11-01 , DOI: 10.1109/msp.2019.2927685
Ibrahim Al-Nahhal , Octavia A. Dobre , Ertugrul Basar , Cecilia Moloney , Salama Ikki

The Gaussian function (GF) is widely used to explain the behavior or statistical distribution of many natural phenomena as well as industrial processes in different disciplines of engineering and applied science. For example, the GF can be used to model an approximation of the Airy disk in image processing, a laser heat source in laser transmission welding [1], practical microscopic applications [2], and fluorescence dispersion in flow cytometric deoxyribonucleic acid histograms [3]. In applied sciences, the noise that corrupts the signal can be modeled by the Gaussian distribution according to the central limit theorem. Thus, by fitting the GF, researchers can develop a sound interpretation of the corresponding process or phenomenon behavior.

中文翻译:

一种用于拟合高斯函数的快速、准确且可分离的方法 [提示和技巧]

高斯函数 (GF) 被广泛用于解释工程和应用科学不同学科中许多自然现象以及工业过程的行为或统计分布。例如,GF 可用于模拟图像处理中的艾里斑近似值、激光传输焊接中的激光热源 [1]、实际微观应用 [2] 以及流式细胞仪脱氧核糖核酸直方图中的荧光色散 [3] ]。在应用科学中,可以根据中心极限定理通过高斯分布对破坏信号的噪声进行建模。因此,通过拟合 GF,研究人员可以对相应的过程或现象行为进行合理的解释。
更新日期:2019-11-01
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