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Stochastic Processes: Theory for Applications
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311
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99%
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R. G. Gallager
On this page
1 · Introduction and review of probability
2 · Poisson processes
3 · Gaussian random vectors and processes
4 · Finite-state Markov chains
5 · Renewal processes
6 · Countable-state Markov chains
7 · Markov processes with countable-state spaces
8 · Detection, decisions, and hypothesis testing
9 · Random walks, large deviations, and martingales
10 · Estimation
Chapter 1
Introduction and review of probability
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48
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100%
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Chapter 2
Poisson processes
[
28
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96%
]
Chapter 3
Gaussian random vectors and processes
[
25
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100%
]
Chapter 4
Finite-state Markov chains
[
38
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100%
]
Chapter 5
Renewal processes
[
47
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100%
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Chapter 6
Countable-state Markov chains
[
18
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100%
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Chapter 7
Markov processes with countable-state spaces
[
33
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100%
]
Chapter 8
Detection, decisions, and hypothesis testing
[
15
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100%
]
Chapter 9
Random walks, large deviations, and martingales
[
43
/
98%
]
Chapter 10
Estimation
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16
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100%
]