Bayesian recursive inference of phase in additive Gaussian noise environments is studied. A tractable conjugate system is established using a von Mises distribution. Its shaping p...
Anthony Quinn, Jean-Pierre Barbot, Pascal Larzabal
What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version...
This paper introduces an application and a methodology to predict future states of a process under real-time requirements. The real-time functionality is achieved by creating a Ba...
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...