In this work, a new algorithm called LP-Neuro method is developed to solve artificial neural network problems. In this algorithm, the weights are obtained by a combination of linear programming having a sparse coefficient matrix and a single variable nonlinear optimization routine. The results are illustrated by solving three different problems, two of which are useful in the on-line control of robotic manipulators.

Issue Section:
Technical Briefs
Topics:
Artificial neural networks, Algorithms, Linear programming, Manipulators, Optimization
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