We describe an enhanced method for the selection of optimal sensor actions in a probabilistic state estimation framework. We apply this to the selection of optimal focal lengths f...
Benjamin Deutsch, Heinrich Niemann, Joachim Denzle...
Recent work has examined the estimation of models of stimulus-driven neural activity in which some linear filtering process is followed by a nonlinear, probabilistic spiking stag...
Jonathan Pillow, Liam Paninski, Eero P. Simoncelli
— In this paper we present an analytical approach to evaluate the symbol error rate (SER) of OFDM systems subject to carrier frequency offset (CFO) and channel estimation error i...
Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...
- We present a low dimensional Bayes probabilistic model for the population of binocular disparity energy neurons centered at the same retinal location, but selective to different ...