Compression methods for approximate stochastic modelling
Understanding of the natural world can be accounted to effective information processing. Natural processes, however, are often riddled with enormous amount of information and high non-linearity. A need to simplify these problems becomes paramount for practical purposes. Computational mechanics has c...
Saved in:
Main Author: | Onggadinata, Kelvin |
---|---|
Other Authors: | Gu Mile |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139314 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Predictive modelling of quantum stochastic processes
by: Huang, Ruocheng
Published: (2021) -
Generalised polynomial chaos approximation for stochastic fractional partial differential equations
by: Teh, Yu Xuan
Published: (2023) -
Quantum-enhanced stochastic analysis
by: Chang, Derek Ding Cong
Published: (2023) -
Time-inconsistent stochastic linear-quadratic control in continuous time
by: Song, Wan Jing
Published: (2021) -
Parabolic systems and stochastic controls: nonlocality, nonlinearity, and time-inconsistency
by: Lei, Qian
Published: (2022)