Strong consistency and convergence rate of parameter identification for bilinear systems

Abstract

This paper discusses the parameter identification problem of discrete-time stochastic bilinear systems, when the dynamic system noise is coloured and its variance function may be unbounded in time. It will be proved, under weak conditions, that the extended least squares estimate of the system parameter has strong consistency and a fast convergence rate.