Signal Processing and Communications Laboratory Skip to content | Access key help Search Signal Processing and Communications Laboratory Department of Engineering University of Cambridge Engineering Department Information Engineering Division (F) Main > Inference Statistical Inference Methods for Signal Processing Background - Projects Faculty Simon Godsill Sumeetpal Singh Postdocs Pete Bunch Fredrik Lindsten James Murphy Research Students Lan Jiang Bernd Kuhlenschmidt Maria Mestre Background Underpinning much of the above applications work is the Bayesian paradigm and associated algorithms for inference about the parameters and structure of complex systems. In the Bayesian approach data is combined with any prior information available in an optimal fashion using probability distributions. We are particularly concerned with the development of new methods appropriate to the applications above. These applications are often sequential in nature (the data arrive one-by-one and a decision/estimate is required with small or no delay), hence we focus considerable attention on sequential learning methods such as Sequential Monte Carlo (particle filtering). Other problems are batch in nature (the data arrive all at once, or we can wait until all of the data have arrived before processing) - in those cases batch algorithms can be used, and we focus attention on stochastic simulation methods such as Markov chain Monte Carlo (MCMC), including those for model uncertainty problems (reversible jump MCMC, etc.). Novel techniques are developed to help tailor these methods to the applications at hand. Projects Some of the current projects in the group: Approximate Bayesian Computation (ABC): using the ABC likelihood for static parameter estimation in Hidden Markov Models Multi-target tracking: new models for interaction, model calibration, applications to Single Molecule Fluorescence Microscopy Particle Markov Chain Monte Carlo (PMCMC) Performance analysis of Sequential Monte Carlo algorithms Parameter learning in Hidden Markov Models: recursive maximum likelihood, online Expectation-Maximization, PMCMC You can find more details by clicking on the individual web-pages of the group's members. Log In Statistical Inference Methods Statistical Inference Methods for Signal Processing BTaRoT: Bayesian Tracking and Reasoning over Time Quick Links Home News History Members Research Teaching Publications Events and Seminars 4th Year Projects Postgraduate Applications Vacancies Contact Us © 2014 University of Cambridge Department of Engineering, Trumpington Street, Cambridge, CB2 1PZ Information provided by div-f-webadmin@eng.cam.ac.uk Privacy policy
