Opuscula Math. 31, no. 4 (2011), 481-499
A mixed integer nonlinear programming formulation for the problem of fitting positive exponential sums to empirical data
Adalys Alvarez
Hugo Lara
Abstract.
In this work we deal with exponential sum models coming from data acquisition in the empirical sciences. We present a two step approach based on Tikhonov regularization and combinatorial optimization, to obtain stable parameter estimations, which fit the data. We develop properties of the solutions, based on their optimality conditions. Some numerical experiments are shown to illustrate our approach.
Keywords:
mixed integer nonlinear programming, regularization, nonlinear least squares.
Mathematics Subject Classification:
90C11, 90C46, 65F22.
About the authors ▼
Adalys Alvarez
Universidad Nacional Abierta, Área de Matemática, Centro Local Lara (Barquisimeto), Venezuela
Hugo Lara
Universidad Centroccidental Lisandro Alvarado, Decanato de Ciencia y Tecnología (Barquisimeto), Venezuela
About the article ▼
Received: 2010-07-20.
Revised: 2010-11-12.
Accepted: 2010-11-26.
Cite this article as ▼
Adalys Alvarez, Hugo Lara, A mixed integer nonlinear programming formulation for the problem of fitting positive exponential sums to empirical data, Opuscula Math. 31, no. 4 (2011), 481-499,
http://dx.doi.org/10.7494/OpMath.2011.31.4.481.
Download this article's citation as: