Speech enhancement is a long standing problem with numerous applications ranging from
hearing aids, to coding and automatic recognition of speech signals. In this survey paper we …

In this self-contained survey/review paper, we systematically investigate the roots of
Bayesian filtering as well as its rich leaves in the literature. Stochastic filtering theory is …

The problem of noise reduction has attracted a considerable amount of research attention
over the past several decades. Among the numerous techniques that were developed, the …

Over the past few years, particle filters have been applied with great success to a variety of
state estimation problems. In this paper we present a statistical approach to increasing the …

Over the last years, particle filters have been applied with great success to a variety of state
estimation problems. We present a statistical approach to increasing the efficiency of particle …

We develop methods for performing smoothing computations in general state-space models.
The methods rely on a particle representation of the filtering distributions, and their evolution …

In two editions spanning more than a decade, The Electrical Engineering Handbook stands
as the definitive reference to the multidisciplinary field of electrical engineering. Our …

Particle methods are a set of powerful and versatile simulation-based methods to perform
optimal state estimation in nonlinear non-Gaussian state-space models. The ability to …

Telecommunication systems and human-machine interfaces start employing multiple
microphones and loudspeakers in order to make conversations and interactions more …

Particle filters estimate the state of dynamical systems from sensor information. In many real
time applications of particle filters, however, sensor information arrives at a significantly …