Examples of 'stochastic processes' in a sentence
Meaning of "stochastic processes"
Stochastic processes are mathematical models that describe the random evolution of a system over time. They are used to analyze and predict outcomes in fields such as finance, physics, and biology
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- plural of stochastic process
How to use "stochastic processes" in a sentence
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stochastic processes
We use a class of stochastic processes called martingales.
Discovering of new asymptotic properties of stochastic processes.
Longini studies stochastic processes applied to epidemiological problems.
The course provides an introduction to stochastic processes.
A special class of stochastic processes are the stationary ones.
It relies exclusively on causal connections and no stochastic processes.
Stochastic processes in continuous time.
Studies concerning relativistic stochastic processes are then displayed.
Stochastic processes in materials engineering.
Statistical inference for stochastic processes.
Stochastic processes play an important role in the dynamics of complex systems.
Differential equations were applied to stochastic processes.
Causality relations between stochastic processes and families of sigma algebras.
We may also define functions on discontinuous stochastic processes.
Study of stochastic processes with applications to physics and complex systems.
See also
All the signals are modeled uing stochastic processes.
O the application of stochastic processes to financial modelling and numerical algorithms.
He is best known for his work on stochastic processes.
Nonlinear deterministic and stochastic processes in dynamics of mechanical systems and applications.
Manufacturing processes are assumed to be stochastic processes.
These are stochastic processes.
The approach presented relies on quantum stochastic processes.
Describe the concepts of stochastic processes in discrete and continuous time.
Both models apply to homogenous stationary stochastic processes.
We used convergence theorem of stochastic processes to highlight different behavior of this model.
Covers the hard modern theory of stochastic processes.
Stochastic processes are mathematical models for random phenomena evolving in time or space.
The finding applies to phenomena described by stochastic processes.
His research is concerned with stochastic processes and their applications in finance.
Gaussian processes are the normally distributed stochastic processes.
For deep results linking theory of stochastic processes with classical mathematical analysis.
This is a rigorous introduction to the theory of stochastic processes.
Applications of stochastic processes to social dynamics constitute a prominent research eld of the last years.
Her research concerns probability theory and stochastic processes.
Challenges related to stochastic processes have been solved using recursive models and neural networks.
This is a ubiquitous measure of roughness in the theory of stochastic processes.
Probability and stochastic processes.
In this thesis intracellular transport is modeled by means of stochastic processes.
It is one of the most popular stochastic processes in reliability theory.
The most common way to create compositions through mathematics is stochastic processes.
Boolean models are also examples of stochastic processes known as coverage processes.
The entropy rate may be used to estimate the complexity of stochastic processes.
In this thesis we study tree di erent stochastic processes describing the brain activity.
Smoluchowski presented an equation which became an important basis of the theory of stochastic processes.
The geometry of periodically correlated stochastic processes induced by the dilation.
Random variates are used when simulating processes driven by random influences stochastic processes.
This dissertation also studies the class of stochastic processes driven by a context tree models.
The first and second parts are dedicated to the statistical inference of stochastic processes.
Diffusions are stochastic processes with continuous paths and can model a large range of intracellular movements.
He is best known for his work on theory of stochastic processes.
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Only that his life processes are ebbing
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Examples of using Stochastic
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Unobserved heterogeneity in stochastic cost frontier models
Stochastic architectures are more favorable at micro scales
An example of a doubly stochastic model is the following
