I am working on an applied project involving intractable inference in temporal Bayesian networks and influence diagrams. We are examining a number of approximate methods. We have identified particle filters as one of the approaches to investigate. We have found a number of references, but they tend to be jargon-filled and require a lot of background even to get started. I would very much like to find something tutorial in nature that would be appropriate for someone with a background in standard engineering math, a knowledge of basic physics, an understanding of Bayesian networks at the applied user level, but no specialized knowledge of statistical physics, advanced statistics, or information theory. Does anyone know of any references like this? If I can't find one, I'll write one, but it would be nice if something existed.
Thanks very much! Kathy Laskey
