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Decision-Directed Multivariate Empirical Bayes Classification With Nonstationary Priors, Wynn C. Stirling, A. Lee Swindlehurst
Decision-Directed Multivariate Empirical Bayes Classification With Nonstationary Priors, Wynn C. Stirling, A. Lee Swindlehurst
Faculty Publications
A decision-directed learning strategy is presented to recursively estimate (i.e., track) the time-varying a priori distribution for a multivariate empirical Bayes adaptive classification rule. The problem is formulated by modeling the prior distribution as a finite-state vector Markov chain and using past decisions to estimate the time evolution of the state of this chain. The solution is obtained by implementing an exact recursive nonlinear estimator for the rate vector of a multivariate discrete-time point process representing the decisions. This estimator obtains the Doob decomposition of the decision process with respect to the a-field generated by all past decisions and corresponds …
Simultaneous System Identification And Decision-Directed Detection And Estimation Of Jump Inputs To Linear Systems, Wynn C. Stirling
Simultaneous System Identification And Decision-Directed Detection And Estimation Of Jump Inputs To Linear Systems, Wynn C. Stirling
Faculty Publications
A decision-directed approach is presented for analyzing linear systems with unknown jump inputs. The system model parameters are estimated using a Kalman filter, and an empirical Bayes detection procedure is introduced to set the detector parameters, resulting in a decision-directed generalized likelihood ratio test coupled with recursive system parameter estimation. Monte Carlo results are presented to validate the performance of the algorithm.