Results 81 to 90 of about 1,528 (105)
Shallow Learning Techniques for Early Detection and Classification of Cyberattacks over MQTT IoT Networks. [PDF]
Díaz-Longueira A +5 more
europepmc +1 more source
A Discrete Informational Framework for Classical Gravity: Ledger Foundations and Galaxy Rotation Curve Constraints. [PDF]
Simons M, Allahyarov E, Washburn J.
europepmc +1 more source
Multidimensional Predictors of Functional Recovery After Curative Colon Cancer Surgery: A Patient-Reported Outcomes Study. [PDF]
Lodi MN +10 more
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Optional Sampling Theorem for Deformed Submartingales
Theory of Probability and Its Applications, 2015Summary: The family \({{\mathbb Q}}=(Q^{(n)}, {\mathcal F}_{n})_{n=0}^{\infty}\) of probability measures \(Q^{(n)}\) defined on \({{\mathcal F}}_{n}\) is considered. It is called a deformation of the first kind if for all \(n\in \{0,1,2,\dots\}\), \(Q^{(n+1)}|_{{{\mathcal F}}_{n}}\ll Q^{(n)}\), and a deformation of the second kind if \(Q^{(n+1)}|_ ...
I V Pavlov
exaly +3 more sources
Generalization of Doob's optional sampling theorem for deformed submartingales
Russian Mathematical Surveys, 2013I V Pavlov, O V Nazarko
exaly +2 more sources
The optional sampling theorem for convex set valued martingales.
Journal Fur Die Reine Und Angewandte Mathematik, 1979exaly +2 more sources
Randomized Stopping Times: DOOB'S Optiomal Sampling Theorem and Optimal Stopping
Mathematische Nachrichten, 1984Consider an optimal stopping problem on a stochastic process \(\{Z_ n\}\), \(n\in N\); a class of randomized stopping times, which includes the class of stopping times, is introduced. First, a generalization of Doob's optional sampling theorem is given for randomized stopping times.
Buckdahn, R., Engelbert, H. J.
openaire +2 more sources

