Quickest Detection of Abrupt Changes

CSC

86150

Quickest Detection of Abrupt Changes

The problem of detecting abrupt changes in the statistical behavior of observation arises in a variety of fields including signal processing, computer vision and finance. Using the mathematical methods of statistical sequential techniques and stochastic optimization, this course describes the fundamental underpinnings of the field providing the background necessary to design analyze and understand quickest detection algorithms and stopping times. In this course we will provide a unified treatment of several different approaches to the quickest detection problem and draw examples from the field of signal processing, finance and computer vision. The course also covers models used in finance and signal processing, Brownian motion, Ito calculus, Markov processes and the fundamental theory of asset pricing. The notion of stopping time and its association with detection algorithms is further examined. Moreover, connections between detection algorithms and drawdown measures are drawn. The course finally examines the use of detection algorithms in online trading and the detection and classification of objects in point clouds of urban scenes.

Offer as needed

Graduate School Graduate

No