LAUSR

Generalized Gaussian distribution (GGD) is one of the most prominent and widely used parametric distributions to model the statistical properties of various phenomena. Parameter estimation for these distributions becomes a fundamental problem. However, most of the existing parameter estimation techniques are centralized. In this paper, we consider distributed parameter estimation for univariate GGD over sensor networks. Parameters among different nodes are estimated cooperatively for the proposed diffusion techniques. Numerical studies are carried out to evaluate the efficiency of the proposed methods, in terms of average root mean square error and convergence rate.