A particle filtering technique for Jump Markov Systems

This paper presents a particle filtering strategy in order to estimate the state of Jump Markov Systems (JMS). These processes are often met in signal communications, when the Bayesian model changes with time. Our algo-rithm takes advantage of the structure of the process.