Direct Method for Estimating Parameters of Two-Segmented Piecewise Logistic Curve

In this study we examine an approach to approximation of experimental data of a two-segmented piecewise logistic curve based on the linear mean square regression. The requirement to use fixed-point arithmetic only in the estimation algorithm is the main condition for the operation in the embedded system. The paper proposes a method for parameters estimation of the piecewise logistic curve with the segment change-point coinciding with the inflection of the logistic functions. At the first stage we estimated the curve inflection point divided the samples of the experimental data into two parts. At the second stage, each part of the data is approximated independently by a generalized logistic function with the given inflection point. As a result, we suggest using a differential equation whose solution is the generalized logistic function in the mean square secondorder regression for estimating the parameters of the curve. The developed method can be used in combination with other known direct computing methods

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