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T9 Quantum Physics Methods For Nonlinear Filtering

Length: 3 hours

Intended Audience: The intended audience are engineers, PhD students, or interested people who are working in the field of statistical signal processing, tracking and fusion.

Description: Relationships between nonlinear filtering and quantum physics has been studied in the past. In this tutorial, more modern connections between the two fields are drawn, particularly based on methods drawn from Feynman path integrals, quantum field theory and renormalization group.

Prerequisites: General familiarity with stochastic processes and multi-variable calculus. No knowledge of quantum physics, or advanced mathematics, such as measure theory, is assumed.

Presenter: Bhashyam Balaji and Fred Daum

Bhashyam Balaji is a Senior Defence Scientist at Defence R&D Canada, and a Senior Member of IEEE. He obtained his Ph.D. in elementary particle theory from Boston University. He has published over 60 technical articles, many in areas related to application of quantum physics methods to nonlinear filtering theory. His other research interests include all aspects of radar sensor outputs, including space-time adaptive processing, multitarget tracking, and meta-level tracking including the application of stochastic context-free grammars to syntactic tracking. His recent research also includes theoretical and applied aspects of multisource data fusion, including tracking and fusion of sensor outputs from radar, EO/IR, acoustic, electronic support measures, and magnetic anomaly detection sensors. He has been an invited speaker to military radar conferences where has also presented tutorials on radar signal processing and multi-target tracking.

Fred Daum is a senior principal Fellow at Raytheon, an IEEE Fellow, a Distinguished Lecturer of the IEEE-AES Society, and a graduate of Harvard University. Fred was awarded the Tom Phillips prize for technical excellence, in recognition of his ability to make complex radar systems work in the real world. He developed, analyzed and tested the real time algorithms for essentially all the large long range phased array radars built by the USA in the last four decades. These real time algorithms include: extended Kalman filters, radar waveform scheduling, Bayesian discrimination, data association, discrimination of satellites from missiles, calibration of tropospheric and ionospheric refraction, and target object mapping. Fred's exact fixed finite dimensional nonlinear filter theory generalizes the Kalman and Beneš filters. He has published nearly one hundred technical papers, and he has given invited lectures at several leading institutions.

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