PARTIAL LIKELIHOOD FOR REAL-TIME SIGNALPROCESSING WITH FINITE NORMAL MIXTURESBo

We introduce a uniied framework for nonlinear signal processing with nite normal mixtures (FNM) by using maximum partial likelihood (MPL) theory. We show that the equivalence of MPL to accumulated relative entropy (ARE) minimization is valid for the FNM. Then, we deene the information geometry of MPL and use the result to derive the em algorithm for… CONTINUE READING