A deep learning approach for the solution of probability density evolution of stochastic systems

A deep learning approach for the solution of probability density evolution of stochastic systems

Derivation of the probability density evolution provides invaluable insight into the behavior of many stochastic systems and their performance. However, for most real-time applications, numerical determination of the probability density evolution is a formidable task. The latter is due to the requir...

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Bibliographic Details
Main Authors: Khodabakhsh, A.H (Author), Pourtakdoust, S.H (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2022
Subjects:
Deep neural network
Deep Neural Network (DNN)
Deep neural networks
Density evolution
Density evolution method
Differential equations
Evolution equations
General density evolution equation
General Density Evolution Equation (GDEE)
Learning systems
Network architecture
Neural-networks
Numerical methods
Physic informed neural network
Physics Informed Neural Network (PINN)
Probability
Probability density evolution method
Probability Density Evolution Method (PDEM)
Probability density evolutions
Probability evolution
Stochastic systems
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