Results 221 to 230 of about 198,332 (267)

Chaotic and Stochastic Components in an Influenza Surveillance Series: Nonlinear Dynamics and Predictive Modeling Study. [PDF]

JMIRx Med
Goncalves CPDS, Rouco C.
europepmc   +1 more source

Topics and Insights on 1-D Tension Stiffening of an RC Member. [PDF]

Materials (Basel)
Yankelevsky DZ, Karinski YS, Tsemakh D, Feldgun VR.   +3 more
europepmc   +1 more source

Confidence estimation as a stochastic process in a neurodynamical system of decision making.

J Neurophysiol, 2015
Wei Z, Wang XJ.
europepmc   +1 more source

Stem Cell Differentiation as a Non-Markov Stochastic Process

Cell Systems, 2017
Colin Please, Ann Babtie, Franz-Josef Müller   +2 more
exaly   +2 more sources

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Detection of stochastic processes

IEEE Transactions on Information Theory, 1998
Summary: This paper reviews two streams of development, from the 1940's to the present, in signal detection theory: the structure of the likelihood ratio for detecting signals in noise and the role of dynamic optimization in detection problems involving either very large signal sets or the joint optimization of observation time and performance.
Thomas Kailath, H. Vincent Poor
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Tunneling as a Stochastic Process

Foundations of Physics, 1998
An alternative model for tunneling processes, based on the capability of the telegrapher’s equation to describe stochastic processes, is able to account for delay time results of an optical experiment at the microwave scale, where superluminal behaviors have been evidenced.
A. Ranfagni, R. Ruggeri, A. Agresti
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Stochastic Processes with Applications

Technometrics, 1992
Preface to the Classics Edition Preface Sample course outline 1. Random walk and Brownian motion 2, Discrete-parameter Markov chains 3. Birth-death Markov chains 4. Continuous-parameter Markov chains 5. Brownian motion and diffusions 6. Dynamic programming and stochastic optimization 7. An introduction to stochastic differential equations 8.
I. G. MacKenzie, R. N. Bhattacharya, E. C. Waymire   +2 more
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Stochastic Processes

2010
A stochastic process is any process describing the evolution in time of a random phenomenon. From a mathematical point of view, the theory of stochastic processes was settled around 1950. Since then, stochastic processes have become a common tool for mathematicians, physicists, engineers, and the field of application of this theory ranges from the ...
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On Modifications of Stochastic Processes

Mathematische Nachrichten, 1984
Let \({\mathcal P}\) be a family of probability measures on a \(\sigma\)-field \({\mathcal F}\) of subsets of \(\Omega\). Extending results known for the case where \({\mathcal P}\) consists of a single probability measure, the author obtains necessary and sufficient conditions for a stochastic process X on (\(\Omega\),\({\mathcal F},{\mathcal P ...
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