The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.
ReBEL is a Matlabtoolkit of functions and scripts, designed to
facilitate sequential Bayesian inference (estimation) in general state
space models. This software consolidates research on new methods for
recursive Bayesian estimation and Kalman filtering by Rudolph van der
Merwe and Eric A. Wan. The code is developed and maintained by Rudolph
van der Merwe at the OGI School of Science & Engineering at OHSU
(Oregon Health & Science University).
This paper deals with the problem of speech enhancement when a
corrupted speech signal with an additive colored noise is the only
information available for processing. Kalman filtering is known as
an effective speech enhancement technique, in which speech signal
is usually modeled as autoregressive (AR) process and represented
in the state-space domain.
