Dr. Jim Candy's Abbreviated Abstract and Biography

Call for Abstracts (pdf)

Electronic Registration Form (.doc)

Abstract Template (.doc)

Dr. James Candy
Abstract and Bio

Prof. Sanjit Mitra
Abstract and Bio

Abstract
In the real world, systems designed to extract signals from noisy measurements are plagued by errors due to constraints of the sensors employed, to random disturbances and noise and, probably most common, to the lack of precise knowledge of the underlying physical phenomenology generating the process in the first place! Methods capable of extracting the desired signal from hostile environments require approaches that capture all of the a priori information available and incorporate them into a processing scheme. These approaches are typically model-based, employing mathematical representations of the component processes involved. However, the actual implementation enabling the processor evolves from the realm of statistical signal processing using a “Bayesian” approach. In this lecture, Dr. Candy will discuss this combination of the Bayesian and model-based approaches to signal and image processing, thereby capturing the underlying physics, instrumentation and noise in the form of mathematical models from which the measured data evolved. He will present a unique perspective of signal processing from the Bayesian approach, starting with a brief tutorial of nonlinear statistical signal processing, through “simulation-based” (Monte Carlo) methods, and leading to the idea of a “particle filter”, which is a discrete representation of a probability distribution. He will present applications that compare the performance of the particle filter designs with classical implementations (nonlinear model-based processors implemented using extended Kalman filters). This novel approach is much more of a modeler’s rather than signal processor’s tool, since we are working directly in the physics of the problem.

Biography
Dr. James V. Candy recently returned to LLNL from a year-long assignment at the University of Cambridge (Clare Hall College) where he was elected as Visiting Fellow. He has been a researcher at LLNL since 1976, holding various positions including from Project Engineer for Signal Processing, Thrust Area Leader for Signal and Control Engineering, CASIS Founder and Director, and most recently Chief Scientist for Engineering. He has supported numerous programs with his research interests in Bayesian estimation, system identification, spatial estimation, signal and image processing, array signal processing, nonlinear signal processing, tomography, sonar/radar and biomedical applications.

Dr. Candy is a Fellow of the IEEE and a Fellow of the Acoustical Society of America (ASA). He received the IEEE Distinguished Technical Achievement Award for the “development of model-based signal processing in ocean acoustics.” He was also recently selected as an IEEE Distinguished Lecturer for oceanic signal processing as well as presenting an IEEE tutorial on advanced signal processing available through their video website courses. Dr. Candy has published over 200 journal articles, book chapters, and technical reports, as well as written three texts in signal processing: “Signal Processing: the Model-Based Approach,” (McGraw-Hill,1986), “Signal Processing: the Modern Approach,” (McGraw-Hill, 1988), and “Model-Based Signal Processing,” (Wiley/IEEE Press, 2006). He is currently the IEEE Chair of the Technical Committee on "Sonar Signal and Image Processing" and was the Chair of the ASA Technical Committee on "Signal Processing in Acoustics" as well as being an Associate Editor for Signal Processing of ASA (on-line).

Dr. Candy received his B.S.E.E. degree from the University of Cincinnati and his M.S.E. and Ph.D. degrees in Electrical Engineering from the University of Florida, Gainesville. He received a commission in the US Air Force in 1967 and was a Systems Engineer/Test Director from 1967 to 1971 before joining the laboratory. He has been an Adjunct Professor at San Francisco State University, the University of Santa Clara, and the UC Berkeley Extension, teaching graduate courses in signal and image processing. He is currently an Adjunct Full-Professor at the University of California, Santa Barbara.

CASIS Current Year | CASIS 2006 | Workshop | Agenda | Abstracts | Presentations