Maximum likelihood estimation of bias in discrete linear systems
Andrew P. Sage, Jin L. Lin · 1970
This paper presents the use of maximum likelihood estimation, optimization theory, and discrete invariant imbedding in the development of algorithms for the maximum likelihood estimation of bias coefficients in discrete linear systems with stochastic inputs and disturbances.