Statistical signal processing applications usually require the estimation of some parameters
of interest given a set of observed data. These estimates are typically obtained either by …

Animals produce sounds for diverse biological functions such as defending territories,
attracting mates, deterring predators, navigation, finding food and maintaining contact with …

Node self-localization is a key research topic for wireless sensor networks (WSNs). There
are two main algorithms, the triangulation method and the maximum likelihood (ML) …

Autonomous acoustic recorders are an increasingly popular method for low‐disturbance,
large‐scale monitoring of sound‐producing animals, such as birds, anurans, bats, and other …

Recent work in wireless embedded networked systems has followed heterogeneous
designs, incorporating a mixture of elements from extremely constrained 8-or 16-bit “Motes” …

Many applications in signal processing require the estimation of some parameters of interest
given a set of observed data. More specifically, Bayesian inference needs the computation …

Emerging high-rate applications (imaging, structural monitoring, acoustic localization) will
need to transport large volumes of data concurrently from several sensors. These …

Monte Carlo methods represent the de facto standard for approximating complicated
integrals involving multidimensional target distributions. In order to generate random …

Bioacoustic monitoring is becoming more and more popular as a non-invasive method to
study populations and communities of vocalizing animals. Acoustic pattern recognition …

Localization is of great importance in mobile and wireless network applications. Time
Difference of Arrival (TDOA) is one of the widely used localization schemes, in which the …