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 240
... electrons with energy E ' ( E ' > E ) enter the interval ( E , EdE ) by radiating part of their energy . This number is dE dt S TE ' , t ) % E ( - E ' E dE ' = dE dt π E ' E ' 프 , 190 ( 0 ) dv ( 5.2 ) 1 v where yo ( v ) , the ...
... electrons with energy E ' ( E ' > E ) enter the interval ( E , EdE ) by radiating part of their energy . This number is dE dt S TE ' , t ) % E ( - E ' E dE ' = dE dt π E ' E ' 프 , 190 ( 0 ) dv ( 5.2 ) 1 v where yo ( v ) , the ...
Page 262
... number of photons to the mean number of electrons . In particular , it has been shown that and Si.2 ( e ' , t ) lim t → ∞ S1 , 1 ( € , t ) - 0 E ' > ε lim Si.2 ( e ' , t ) t → ∞ Si , 1 ( E , t ) ( 5.85 ) ( 5.86 ) The second result ...
... number of photons to the mean number of electrons . In particular , it has been shown that and Si.2 ( e ' , t ) lim t → ∞ S1 , 1 ( € , t ) - 0 E ' > ε lim Si.2 ( e ' , t ) t → ∞ Si , 1 ( E , t ) ( 5.85 ) ( 5.86 ) The second result ...
Page 264
... electron - photon cascades the characteristic functional will have two arbitrary argument functions , say μ ( E ) and ŋ ( E ) , associated with the random variables representing the number of electrons and photons , respectively . Hence ...
... electron - photon cascades the characteristic functional will have two arbitrary argument functions , say μ ( E ) and ŋ ( E ) , associated with the random variables representing the number of electrons and photons , respectively . Hence ...
Contents
Introduction | 1 |
THEORY | 7 |
Processes Discrete in Space and Continuous in Time | 53 |
Copyright | |
16 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 applications arrival assume assumptions asymptotic birth process birth-and-death process boundary branching processes cascade process cascade theory coefficient collision consider counter defined denote the number denote the probability derive determined deterministic differential equation diffusion equations diffusion processes distribution function E₁ electron electron-photon cascades energy epidemic equilibrium exists expression Feller finite functional equation given Hence initial condition integral equation interval 0,t ionization joins the queue Kendall Kolmogorov equations Laplace transform Laplace-Stieltjes transform Let the random limiting distribution Markov chain Markov processes Math matrix Mellin transform Monte Carlo methods nonnegative nucleon o(At obtain P₁ parameter particle photon Phys Poisson process population probability distribution Proc product density queueing process queueing system Ramakrishnan random variable random variable X(t recurrent repairman satisfies Statist stochastic model Stochastic Processes t₁ Takács Theorem tion transition probabilities x₁ zero