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Sequential Inference with Particle Filters
Speaker: Mahesan Niranjan
Affiliation: The University of Sheffield
Description: Many modern signal processing problems involve systems that are nonlinear and nonstationary. Data-driven models that are based on powerful function approximation methods such as neural networks have been applied with demonstrable success to these problems. Nonstationarity imposes a particular difficulty in these settings because regularization techniques such as cross validation can be inapplicable. This tutorial will address sequential estimation techniques that are useful in nonlinear and nonstationary environments. It will use a Bayesian dynamical systems approach and will introduce concepts and algorithms involving the extended Kalman filter (EKF) and powerful variants of it. Starting from the EKF, we will review more recent developments in sequential Markov Chain Monte Carlo (Particle Filters), and explore their application in a number of practical examples taken from speech signal and speech processing.
Presenter biography: Mahesan Niranjan received his BSc from the University of Peradeniya, SriLanka (1982) and MEE from Eindhoven, The Netherlands (1985), both in Electronics Engineering. His PhD was from the University of Cambridge, England (1990). After eight years as lecturer in the Cambridge University Engineering Department, he was appointed to a Professorship in Computer Science in The University of Sheffield, where also served as Head of the Department of Computer Science. In Sheffield he leads a member of a research group in Machine Learning which includes three members of Faculty, three post-doctoral research assistants and ten PhD candidates. His research interests are in Nonlinear & Nonstationary Signal Processing and Statistical Pattern Recognition. He has worked on the algorithmic aspects as well as on a range of applications including Speech Processing, Medical Diagnostics and Computational Finance. More recently he is interested in problems in Computational Biology and works closely with a team of Developmental Biologists in Sheffield.
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