## 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 325

The probability of scattering is ayti(l)e-1* A* + o(At) In the above, a = VMjffl and m

is the mass of the

the case of scattering, the increase of the lethargy of the

The probability of scattering is ayti(l)e-1* A* + o(At) In the above, a = VMjffl and m

is the mass of the

**neutron**. It is also assumed that the collisions are such that, inthe case of scattering, the increase of the lethargy of the

**neutron**is independent ...Page 330

where m is the actual mass of the

change per collision, and 1, is the average of the scattering mean free path, i.e.,

the average distance the

where m is the actual mass of the

**neutron**, f is the average logarithmic energychange per collision, and 1, is the average of the scattering mean free path, i.e.,

the average distance the

**neutron**travels between collisions. F. Other Studies.Page 351

As a branch of mathematical physics its most important applications are to

astrophysical and

radiant energy is generally assumed to be a photon, while in

theory the ...

As a branch of mathematical physics its most important applications are to

astrophysical and

**neutron**transport problems. In astrophysics the carrier ofradiant energy is generally assumed to be a photon, while in

**neutron**transporttheory the ...

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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