Pulling the information out of the clutter
Abstract
Fixed and wireless telecommunications systems, sonar systems, navigation devices, image processing algorithms-these are all examples of where signal processing is used. Much signal processing is based on statistical models of processes generating the signals and the contaminating noise. This paper traces the development of statistical processing theories, beginning with Wiener filtering, continuing through Kalman filtering, and ending with Hidden Markov Models. Different assumptions underpin these theories, and also very different mathematics. Yet a number of common features remain.
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Applied Mathematics Entering the 21st Century: Invited Talks from the ICIAM 2003 Congress
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