Sparse approximation based Gaussian mixture model approach for uncertainty propagation for nonlinear systems
Vishwajeet Kumar, Puneet Singla · 2013
A new method is proposed to determine the number of components that are sufficient to estimate the probability density function of a non-linear dynamic system using Gaussian sum filter. This method is based upon the combination of L1and L2norm. While L1norm tries to shift the solution towards one of the vertices of the simplex, thus, minimizing the number of non-zero quantities, the L2norm tries to reduce the error to as low as possible. Unlike previous methods, the method proposed in this paper is simple and computationally less expensive.