Neural network modeling of vector multivariable functions in ill-posed approximation problems. View at Publisher" BibTeX export " Download " More... Journal of Computer and Systems Sciences International Volume 52, Issue 4, July 2013, Pages 503-518

A neural network solution of the ill-posed inverse approximation problem of a multivariable vector function based on of a committee of multilayer perceptrons is proposed. A nonlinear adaptive decision-making rule by the committee is developed that improves the accuracy compared with other neural network solutions of the inverse problem. Using a model example, the accuracy characteristics of the method are shown. An applied engineering problem is considered and the results of its solution by the proposed method are presented.
Indexed keywords
Adaptive decision making; Approximation problems; Engineering problems; Multi variables; Multivariable functions; Network solutions; Neural network model; Vector functions