We study the behaviour of an infinite system of ordinary differential equations modelling the dynamics of a meta-population, a set of (discrete) populations subject to local catastrophes and connected via migration under a mean field rule; the local population dynamics follow a generalized logistic law. We find a threshold below which all the solutions tend to total extinction of the meta-popul...

We present a method for building an initial phoneme model for training an HMM in a new language using an already trained recognition system in a base language. HMM based phoneme recognition systems are used to model the phonemes in most large vocabulary speech recognition tasks. Mappings between the phonetic spaces of the two languages are generated and are used to populate the phonetic space o...

Detecting and localizing selective sweeps based on SNP data has recently received considerable attention. Here we introduce the use of Hidden Markov Models (HMMs) for the detection of selective sweeps in DNA sequences. Like previously published methods, our HMMs use the site frequency spectrum, and the spatial pattern of diversity along the sequence, to identify selection. In contrast to earlie...

This paper uses the theory of large deviations to analyse equilibrium selection in one-dimensional games with large populations where the system evolves according to a jump Markov process. The equilibria selected maximise a quasi-potential function which can be determined by solving a polynomial equation. Estimates of waiting times are also given. It shows that the equilibria about which there ...

— The aim of the present paper is to document the need for adapting the definition of hidden Markov models (HMM) to population studies, which rigorous interpretation typically requires the use of mixed-effects models, as well as for corresponding learning methodologies. In this article, mixed hidden Markov models (MHMM) are introduced through a brief state of the art on hidden Markov models and...