High-Order Deep Recurrent Neural Network With Hybrid Layers for Modeling Dynamic Behavior of Nonlinear High-Frequency Circuits-Reference-Cited by-同舟云学术

High-Order Deep Recurrent Neural Network With Hybrid Layers for Modeling Dynamic Behavior of Nonlinear High-Frequency Circuits

Author:

Charoosaei Fatemeh¹,Noohi Mostafa²,Sadrossadat Sayed Alireza¹^ORCID,Mirvakili Ali²^ORCID,Na Weicong³^ORCID,Feng Feng⁴^ORCID

Affiliation:

1. Department of Computer Engineering, Yazd University, Yazd, Iran

2. Department of Electrical Engineering, Yazd University, Yazd, Iran

3. Faculty of Information Technology, Beijing University of Technology, Beijing, China

4. School of Microelectronics, Tianjin University, Tianjin, China

Funder

National Natural Science Foundation of China

Scientific Research Project of Beijing Educational Committee

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation

Link

Reference43 articles.

1. On the difficulty of training recurrent neural networks;pascanu;Proc Int Conf Mach Learn,2013

3. Recurrent neural networks hardware implementation on FPGA;chang;arXiv 1511 05552,2015

4. MuProp: Unbiased backpropagation for stochastic neural networks;gu;arXiv 1511 05176,2015

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

4. Echo State Networks for Accurate and Efficient Modeling of Dynamic Circuits;2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS);2024-04-22