As an approach to feature estimation, exponential fitting has attracted research interests in mathematical modeling. Semantic networks are used for numerous applications in computers, physics, and biology. However, such applications may have fitting troubles with various mathematical tools. Therefore, we present a novel method of fitting 2n data points of a signal to a sum of n exponential functions. The experiments proved that the proposed method operated well for linear and nonlinear functions, as its algorithm was straightforward, practical, and easy to determine. At the same time, the computational intricacy was considerably low, which has specific worth in use.
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