## Elements of the theory of Markov processes and their applicationsGraduate-level text and reference in probability, with numerous scientific applications. Nonmeasure-theoretic introduction to theory of Markov processes and to mathematical models based on the theory. Appendixes. Bibliographies. 1960 edition. |

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Page 315

From R(x) and S(x) the

chamber, say P(x), can be obtained, since P(x) = \ Jo R(x - y) dS(y) (6.91) o Let V

denote the recording or registration level of the discriminator which follows the ...

From R(x) and S(x) the

**distribution function**of the output voltage of the ionizationchamber, say P(x), can be obtained, since P(x) = \ Jo R(x - y) dS(y) (6.91) o Let V

denote the recording or registration level of the discriminator which follows the ...

Page 390

The expression for the Laplace-Stieltjes transform of F*(w) is equivalent to the

solution obtained by Khintchine [41]. If, following Khintchine, we assume that for

Xft < 1 the limiting

obtained ...

The expression for the Laplace-Stieltjes transform of F*(w) is equivalent to the

solution obtained by Khintchine [41]. If, following Khintchine, we assume that for

Xft < 1 the limiting

**distribution function**F*(w) exists, then Eq. (9.38) can beobtained ...

Page 391

If n = 0, only one customer is served, and the associated

x). If re > 1, the server, after serving the first customer, starts to attend one of the

customers waiting in the queue. Let 0„(x) denote the w-fold convolution of 0(x), ...

If n = 0, only one customer is served, and the associated

**distribution function**is H(x). If re > 1, the server, after serving the first customer, starts to attend one of the

customers waiting in the queue. Let 0„(x) denote the w-fold convolution of 0(x), ...

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### Contents

Introduction | 1 |

Processes Discrete in Space and Time | 9 |

Processes Discrete in Space and Continuous in Time | 57 |

Copyright | |

10 other sections not shown

### Other editions - View all

Elements of the Theory of Markov Processes and Their Applications A. T. Bharucha-Reid Limited preview - 2012 |

Elements of the Theory of Markov Processes and Their Applications Albert T. Bharucha-Reid Limited preview - 1997 |

### Common terms and phrases

absorber Acad applications associated assume assumptions asymptotic birth process birth-and-death process branching processes cascade process cascade theory coefficient collision consider defined denote the number denote the probability derive determined deterministic differential equation diffusion equations diffusion processes distribution function electron-photon cascades epidemic exists expression Feller finite fluctuation problem functional equation given Hence initial condition integral equation interval ionization Kendall Kolmogorov equations Laplace transform Laplace-Stieltjes transform Let the random machine Markov chain Markov processes Math mathematical matrix mean and variance mean number Mellin transform Messel method Monte Carlo methods mutation neutron nonnegative nucleon nucleon cascades number of electrons number of individuals o(At obtain parameter photon Phys Poisson process probability distribution Proc Px(t queueing process queueing system radiation Ramakrishnan random variable random variable X(t reaction recurrent refer satisfies solution of Eq Statist stochastic model Stochastic Processes Theorem tion transition probabilities zero