title: A linear method for the curve fitting of multiexponentials.
abstract: 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.
authors.affiliation: NeuroMechanics Research Group, East Tennessee State University, Johnson City 37614-0658, USA. KnisleyJ@NURSSERV.ETSU.TN.edu
authors.forename: J R
authors.initials: JR
authors.lastname: Knisley
authors.forename: L L
authors.initials: LL
authors.lastname: Glenn
mesh_terms: D000465:Algorithms; D005583:Fourier Analysis; D016014:Linear Models; D008959:Models, Neurological; D015233:Models, Statistical; D012044:Regression Analysis