Quickest Detection by H. Vincent Poor and Olympia Hadjiliadis

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http://www.amazon.com/Quickest-Detection-H-Vincent-Poor/dp/0521621046/ref=ntt_at_ep_dpt_2

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1 Introduction 1
2 Probabilistic framework 6
2.1 Introduction 6
2.2 Basic setting 6
2.2.1 Probability spaces 6
2.2.2 Random variables 7
2.2.3 Expectation 8
2.2.4 Radon–Nikodym derivatives 10
2.2.5 Conditional expectation and independence 11
2.2.6 Random sequences 15
2.3 Martingales and stopping times 18
2.3.1 Martingales 19
2.3.2 Stopping times 24
2.3.3 Continuous-time analogs 26
2.4 Brownian motion and Poisson processes 27
2.4.1 Brownian motion 28
2.4.2 Poisson processes 30
2.5 Continuous-time semimartingales 32
2.6 Stochastic integration 34
3 Markov optimal stopping theory 40
3.1 Introduction 40
3.2 Markov optimal stopping problems 40
3.3 The finite-horizon case: dynamic programming 41
3.3.1 The general case 41
3.3.2 The Markov case 46

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3.4 The infinite-horizon case 50
3.4.1 A martingale interpretation of the finite-horizon results 51
3.4.2 The infinite-horizon case for bounded reward 52
3.4.3 The general infinite-horizon case 55
3.4.4 The infinite-horizon case with Markov rewards 59
3.5 Markov optimal stopping in continuous time 60
3.6 Appendix: a proof of Lemma 3.8 61
4 Sequential detection 65
4.1 Introduction 65
4.2 Optimal detection 65
4.3 Performance analysis 74
4.4 The continuous-time case 81
4.4.1 The Brownian case 81
4.4.2 The Brownian case – an alternative proof 86
4.4.3 An interesting extension of Wald–Wolfowitz 90
4.4.4 The case of Itˆo processes 91
4.4.5 The Poisson case 93
4.4.6 The compound Poisson case 100
4.5 Discussion 101
5 Bayesian quickest detection 102
5.1 Introduction 102
5.2 Shiryaev’s problem 103
5.3 The continuous-time case 109
5.3.1 Brownian observations 109
5.3.2 Poisson observations 115
5.4 A probability maximizing approach 122
5.5 Other penalty functions 124
5.6 A game theoretic formulation 125
5.7 Discussion 128
6 Non-Bayesian quickest detection 130
6.1 Introduction 130
6.2 Lorden’s problem 130
6.3 Performance of Page’s test 142
6.4 The continuous-time case 144
6.4.1 Brownian observations 144
6.4.2 Itˆo processes 150
6.4.3 Brownian motion with an unknown drift parameter 152
6.4.4 Poisson observations 154

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6.5 Asymptotic results 157
6.5.1 Lorden’s approach 158
6.5.2 Brownian motion with two-sided alternatives 167
6.6 Comments on the false-alarm constraint 171
6.7 Discussion 172
7 Additional topics 174
7.1 Introduction 174
7.2 Decentralized sequential and quickest detection 175
7.2.1 Decentralized sequential detection with a fusion center 176
7.2.2 Decentralized quickest detection with a fusion center 184
7.2.3 Decentralized sequential detection without fusion 189
7.3 Quickest detection with modeling uncertainty 194
7.3.1 Robust quickest detection 194
7.3.2 Adaptive quickest detection 200
7.4 Quickest detection with dependent observations 201
7.4.1 Quickest detection with independent likelihood ratio sequences 201
7.4.2 Locally asymptotically normal distributions 203
7.4.3 Sequential detection (local hypothesis approach) 205
7.4.4 Quickest detection (local hypothesis approach) 210
Bibliography 213
Index 225

fpga_sh

谢谢楼主提供资料

evotoup

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matrix_er

大牛poor的书一定要看