Dynamical system parameter identification using deep recurrent cell networks: Which gated recurrent unit and when?
E Akagündüz, O Cifdaloz - Neural Computing and Applications, 2021 - Springer
In this paper, we investigate the parameter identification problem in dynamical systems
through a deep learning approach. Focusing mainly on second-order, linear time-invariant …
through a deep learning approach. Focusing mainly on second-order, linear time-invariant …
Applying neural networks for plant model simulation in embedded control system
C Cheng, Y Nakamoto - 2021 IEEE Intl Conf on Dependable …, 2021 - ieeexplore.ieee.org
In debugging and testing the control software used in distributed embedded systems such
as automotive systems, simulations are conducted if the plants to be controlled are …
as automotive systems, simulations are conducted if the plants to be controlled are …
A Performance Comparison of LSTM and Recursive SID Methods in Thermal Modeling of Implantable Medical Devices
This paper investigates application of long short-term memory (LSTM) and recursive system
identification (RSID) algorithms to predict the thermal dynamics of bio-implants, eg UEA …
identification (RSID) algorithms to predict the thermal dynamics of bio-implants, eg UEA …