Knisley J R, Glenn L L
NeuroMechanics Research Group, East Tennessee State University, Johnson City 37614-0658, USA.
J Neurosci Methods. 1996 Aug;67(2):177-83.
Two single-pass methods for fitting multiexponentials to experimental data are described. These methods rely on the construction of a matrix whose characteristic polynomial is used to determine the rates of decay. In the first method, which we call the multiple-delay method, the matrix is constructed using time delays of the experimental data. This method is fast and highly accurate even if the experimental signal contains exponential components with similar rates of decay. In the second method, which we call the successive-integral method, the matrix is constructed using integrals of the experimental data. This procedure yields good results for noisy signals and is a generalization of the method of Martin et al. ((1993) J. Neurosci. Methods, 51: 135-146). In addition, a particular instability of the multiexponential curve fitting problem is identified and a method for overcoming this instability is given.
本文描述了两种将多指数函数拟合到实验数据的单通道方法。这些方法依赖于构建一个矩阵,其特征多项式用于确定衰减率。在第一种方法中,我们称之为多重延迟法,该矩阵是利用实验数据的时间延迟构建的。即使实验信号包含衰减率相似的指数成分,该方法也快速且高度准确。在第二种方法中,我们称之为逐次积分法,该矩阵是利用实验数据的积分构建的。此过程对于噪声信号能产生良好结果,并且是Martin等人((1993)《神经科学方法杂志》,51: 135 - 146)方法的推广。此外,还识别出了多指数曲线拟合问题的一种特殊不稳定性,并给出了克服这种不稳定性的方法。