Polynomial filtering for stochastic non-Gaussian descriptor systems

Stochastic descriptor systems, also named singular systems, have been widely investigated and many important results in the linear filtering theory have been achieved in the framework of Gaussian processes. Nevertheless, such results could be far from optimal, especially in the case of highly asymmetrical non Gaussian noises. This paper presents a polynomial solution for filtering singular systems affected by non-Gaussian noises. The performance of polynomial filters can be improved by increasing their degree. Simulation results support theoretical results.