## 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. |

### From inside the book

Results 1-3 of 22

Page 300

of electron multipliers, scintillation or crystal

addition to assuming that the

**counters**and mechanical recorders, and Type II**counters**are used in the theoryof electron multipliers, scintillation or crystal

**counters**, and electronic amplifiers. Inaddition to assuming that the

**counter**is either Type I or Type II, it is usually ...Page 305

In applying the general theory to Type II

distribution function F(t) is unknown, since by ... This condition will obtain if a

large number of impulses arrive at the

first ...

In applying the general theory to Type II

**counters**we first observe that thedistribution function F(t) is unknown, since by ... This condition will obtain if a

large number of impulses arrive at the

**counter**in rapid succession following thefirst ...

Page 332

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 31 32 33 34 Hammersley,

J. M.: On

Distribution of the Number of Discharges Counted by a Geiger-Müller

a ...

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 31 32 33 34 Hammersley,

J. M.: On

**Counters**with Random Dead Time: I, ... Kosten, L.: On the FrequencyDistribution of the Number of Discharges Counted by a Geiger-Müller

**Counter**ina ...

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### Contents

Introduction | 1 |

Processes Discrete in Space and Continuous in Time | 57 |

Processes Continuous in Space and Time | 129 |

Copyright | |

9 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 addition applications approach arrival associated assume assumptions becomes birth boundary branching processes called cascade coefficients collision concerned condition consider constant continuous counter death defined denote density derive described determined developed differential equation diffusion discussion distribution function electron energy epidemic equal exists expected expression finite fluctuation given gives growth Hence independent individuals initial condition integral interest interval introduce Kolmogorov equations Laplace transform length limit machine Markov Markov chain Markov processes Math mathematical mean method moments necessary nucleon obtain particle particular photon Poisson population positive primary problem Proof properties queueing radiation random variable reaction refer relation represent respectively satisfies shown simple ſº solution Statist Stochastic Processes Theorem theory tion transition probabilities zero