## Proceedings of the International School of Physics "Enrico Fermi". |

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Page 37

between the continuous-time chain N(t) and the discrete-time chain J(k) of

considerable algorithmic and theoretical

all the matrices a, commute with each other and with p(t). All have the same zero

...

between the continuous-time chain N(t) and the discrete-time chain J(k) of

considerable algorithmic and theoretical

**value**. Note that a, = I +**Q**[v implies thatall the matrices a, commute with each other and with p(t). All have the same zero

...

Page 75

Mathematics of fault tree analysis. Boolean switching theory is basic for the

mathematics of fault tree analysis. For the fault tree node set U= [1, 2,

.,x„ be Boolean variables assuming

5,

Mathematics of fault tree analysis. Boolean switching theory is basic for the

mathematics of fault tree analysis. For the fault tree node set U= [1, 2,

**q**], let Xi,xt,...,x„ be Boolean variables assuming

**values**0 or 1 and let * = = (xlfxtt ...,xa). (In fig.5,

**q**...Page 386

Summing

, together with the prior distribution for ... Assume that N is degenerate at a known

Summing

**q**from k to oo, we obtain the probability of the observed outcome which, together with the prior distribution for ... Assume that N is degenerate at a known

**value**, say n, and that A has a gamma distribution witli scale parameter /j, and ...### What people are saying - Write a review

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### Contents

System Eeliabujty | 3 |

Statistical Theory of Eeliablitt | 8 |

Definitions and characterizations | 12 |

Copyright | |

39 other sections not shown

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### Common terms and phrases

algorithm approach associated assume assumption Bayesian boundary points chain coherent system complex conjugate prior consider correctness defined denote detected discussed edited equations equivalence class ergodic errors example exponential distribution failure rate Fault Tree Analysis function gamma given human reliability IEEE Trans IFEA implementation increasing independent input domain integration interval likelihood Markov Markov chain matrix mean method modules monotone month2 N. D. Singpurwalla number of failures number of system NUMITEMS observed obtained operational output parameters phase Poisson Poisson process possible predictive prior distribution probability problem procedure Proschan R. E. Barlow random variables reliability growth models reliability theory renewal theory repair requirements sample sect sequence Software Eng software reliability software reliability models specification Stat statistical stochastic stochastic process subsection system failure system reliability techniques theorem tion tt tt values vector zero