Parameter estimation for nonlinear stochastic model using generalized entropy optimization principle
Yunlong Liu, Lei Guo, Yumin Zhang · 2012
A new type of parameter estimation method has been proposed for a class of nonlinear stochastic model with non-Gaussian disturbance The Parzen window method was first used to estimate the density function of the sampled data and then the generalized entropy optimization p rincip le was used to estimate the unknown parameters. No matter what distribution the noise obeys to, Gaussian or non-Gaussian, unbiased parameter estimated values can be obtained. The simulation results show t he effect iveness of the proposed app roaches.