This unified treatment of the quickest detection problem provides the background necessary to design, analyze, and understand quickest detection algorithms.

H. Vincent Poor is Michael Henry Strater University Professor of Electrical Engineering, and Dean of the School Engineering and Applied Science, at Princeton University, New Jersey, from which he received his PhD in 1977. Prior to joining the Princeton faculty in 1990, he was on the faculty of the University of Illinois, Urbana-Champaign, and has held visiting positions at a number of other institutions, including Imperial College, Harvard University, Massachusetts and Stanford University, California. He is a Fellow of the IEEE, the Institute of Mathematical Statistics, and the American Academy of Arts and Sciences, as well as a member of the US National Academy of Engineering.

1. Introduction; 2. Probabilistic framework; 3. Markov optimal stopping theory; 4. Sequential detection; 5. Bayesian quickest detection; 6. Non-bayesian quickest detection; 7. Additional topics.