Ionizing radiation detection using jump markov linear systems

The systems commonly used to detect photons and estimate their energies are usually irrelevant for high flux. Hidden Markov model and jump Markov linear systems (JMLS) provide a framework which allows us to get an optimal estimate for stochastic processes, whose occurrences are randomly distributed according to time of detection, length and magnitude. It is perfectly adapted to the spectrometry issue. We use the maximum a posteriori (MAP) criterion to estimate the state vector. In the high signal-to-noise ratio (SNR) case, the system can be simplified as a Kalman smoother set up in an on-line version in our lab. An extension in low SNR case is proposed