Faculty of Mathematics and Physics, Institute of Physics, Charles University, Ke Karlovu 5, 121 16 Prague 2, Czech Republic.
J Fluoresc. 2011 May;21(3):873-81. doi: 10.1007/s10895-009-0589-1. Epub 2010 Jan 12.
We tested a Maximum Entropy Method developed for oversampled data (SVD-MEM) on complex analytically simulated exponential decay data consisting of both noisy and noiseless multi-exponential fluorescence decay curves. We observed recovery of simulated parameters for three sets of data: a decay containing three exponential functions in both intensity and anisotropy curves, a set of intensity decays composed of 4, 5 and 6 exponential functions, and a decay characterized by a Gaussian lifetime distribution. The SVD-MEM fitting of the noiseless data returned the simulated parameters with the high accuracy. Noise added to the data affected recovery of the parameters in dependence on a data complexity. At selected realistic noise levels we obtained a good recovery of simulated parameters for all tested data sets. Decay parameters recovered from decays containing discrete lifetime components were almost independent of the value of the entropy scaling parameter γ used in the maximization procedure when it changed across the main peak of its posterior probability. A correct recovery of the Gaussian shaped lifetime distribution required selection of the γ-factor which was by several orders of magnitude larger than its most probable value to avoid a band splitting.
我们测试了一种针对过采样数据开发的最大熵方法(SVD-MEM),该方法应用于由噪声和无噪声多指数荧光衰减曲线组成的复杂解析模拟指数衰减数据。我们观察了三组数据的模拟参数恢复情况:一组强度和各向异性曲线中包含三个指数函数的衰减,一组由 4、5 和 6 个指数函数组成的强度衰减,以及一个具有高斯寿命分布的衰减。SVD-MEM 对无噪声数据的拟合以高精度返回了模拟参数。数据中添加的噪声会影响参数的恢复情况,具体取决于数据的复杂性。在选定的现实噪声水平下,我们对所有测试数据集都获得了模拟参数的良好恢复。从包含离散寿命分量的衰减中恢复的衰减参数几乎与在最大似然过程中使用的熵缩放参数 γ 的值无关,当它穿过其后验概率的主峰时。要正确恢复高斯形状的寿命分布,需要选择 γ 因子,该因子比其最可能值大几个数量级,以避免带宽分裂。