Results 231 to 240 of about 198,332 (267)

The Theory of Stochastic Processes.

The Statistician, 1966
The Theory of Stochastic Processes. By D. R. Cox and H. D. Miller. London, Methuen, 1965. x, 398 p. 914″ 70s.
Zakkula Govindarajulu, D. R. Cox, H. D. Miller   +2 more
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Stochastic Process Creation

2009
In many areas of computer science entities can "reproduce", "replicate", or "create new instances". Paramount examples are threads in multithreaded programs, processes in operating systems, and computer viruses, but many others exist: procedure calls create new incarnations of the callees, web crawlers discover new pages to be explored (and so "create"
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EXCITOTOXICITY AS A STOCHASTIC PROCESS

Clinical and Experimental Pharmacology and Physiology, 1995
SUMMARY1. Neuronal death following excitotoxic insult appears to be a stochastic process involving transition through an intermediate biochemical state.2. Hydrogen ion accumulation in the hours after toxic glutamate exposure may indicate that this transition has occurred.
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Stochastic Processes in Electrochemistry

Analytical Chemistry, 2016
Stochastic behavior becomes an increasingly dominant characteristic of electrochemical systems as we probe them on the smallest scales. Advances in the tools and techniques of nanoelectrochemistry dictate that stochastic phenomena will become more widely manifest in the future.
Pradyumna S. Singh, Serge G. Lemay
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Research in Stochastic Processes.

1983
Abstract : Research was conducted and directed in the area of stochastic processes by three Principal Investigators and their associates, and in estimation in statistical models. The main areas of research activity for each Principal Investigator and co-workers are as follows: (1) Asymptotic optimal quantizers, complex symmetric stable variables and ...
M. R. Leadbetter, Gopinath Kallianpur, Raymond J. Carroll, Stamatis Cambanis   +3 more
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Inference and stochastic processes

Journal of the Royal Statistical Society. Series A (General), 1967
The relation of statistical inference to the wider problem of all inductive inference is reviewed. For scientific inference in general the competing approaches are the hypothetical-deductive and the Bayesian, and the formalism of each is discussed in statistical contexts in terms of the two main concepts of probability—chance and degree of belief.
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Introduction To Stochastic Processes

2006
As discussed in Section 1.5, the characterization of observables as random variables is ubiquitous in descriptions of physical phenomena. This is not immediately obvious in view of the fact that the physical equations of motion are deterministic and this issue was discussed in Section 1.5.1.
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Relativistic Stochastic Processes

Journal of Mathematical Physics, 1968
Relativistic stochastic processes in μ-space are defined and studied in a completely (and manifestly) covariant manner, without particularizing the time variable. It is shown that a number of usual definitions such as ``Gaussian process,'' etc., cannot be given a fully invariant meaning. Markovian processes are also studied.
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An artificial neural network supported stochastic process for degradation modeling and prediction

Reliability Engineering and System Safety, 2021
Shaoping Wang
exaly  

Time-dependent reliability assessment of aging structures considering stochastic resistance degradation process

Reliability Engineering and System Safety, 2022
C S Cai, Yiming Yang, Jianren Zhang
exaly