Software for particle filtering and dynamic mixtures of Gaussians

[Nando de Freitas]

Dear Connectionists,

I've made available some matlab code on particle filtering (aka
condensation, survival of the fittest, bootstrap filters, sequential
Monte Carlo) and a substantial better algorithm when the model at hand
is a dynamic conditionally Gaussian representation. The latter algorithm
is known as Rao Blackwellised particle filtering. This algorithm can be
interpreted as an efficient stochastic mixture of Kalman filters. That
is, as a stochastic bank of Kalman filters. Needless to say, dynamic
mixtures of Gaussians arise in many settings, including computer vision,
speech processing, music processing, fault diagnosis, and so on.

The software also includes efficient state-of-the-art resampling
routines. These are generic and suitable for any application of particle
filters.

The matlab code and links to papers are available at

http://www.cs.ubc.ca/~nando/software.html

Best,
Nando