Measuring system entropy with a deep recurrent neural network model

In this paper, a methodology for assessing the unpredictability of systems with memory was developed. The proposed approach consists in approximating the probability distribution exhibited by the response of a system, understood as a stochastic process, with a deep recurrent neural network; such net...

Full description

Saved in:
Bibliographic Details
Main Authors: Miguel Martinez-Garcia, Eve Zhang, Kenji Suzuki, Yudong Zhang
Format: Default Conference proceeding
Published: 2020
Subjects:
Recurrent neural networks
Entropy analysis
Long short-term memory
Condition monitoring
Deep learning
Online Access:https://hdl.handle.net/2134/15073596.v1
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items