Asymptotic mean‐square boundedness of the numerical solutions for stochastic complex‐valued neural networks with jumps-Reference-Cited by-同舟云学术

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Asymptotic mean‐square boundedness of the numerical solutions for stochastic complex‐valued neural networks with jumps

Published:2022-03-05 Issue:11 Volume:45 Page:6918-6934
ISSN:0170-4214
Container-title:Mathematical Methods in the Applied Sciences
language:en
Short-container-title:Math Methods in App Sciences

Author:

Li Qiang¹,Dong Yiping²,Wang Lan³^ORCID,Cao Jinde⁴⁵^ORCID

Affiliation:

1. School of Science Anhui Agricultural University Hefei China

2. China Key System Co., Ldt. Wuxi China

3. Department of Fundamental Courses Wuxi Institute of Technology Wuxi China

4. School of Mathematics Southeast University Nanjing China

5. Yonsei Frontier Lab Yonsei University Seoul South Korea

Funder

“333 Project” of Jiangsu Province

Natural Science Research of Jiangsu Higher Education Institutions of China

Publisher

Wiley

Subject

General Engineering,General Mathematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mma.8216

Reference44 articles.

1. Dynamics of fully complex-valued neural networks

2. An Augmented Extended Kalman Filter Algorithm for Complex-Valued Recurrent Neural Networks

3. Formulation of quantum effects by using a complex-valued equivalent circuit

4. Exponential synchronization of complex‐valued complex networks with time‐varying delays and stochastic perturbations via time‐delayed impulsive control;Zhang L;Appl Math Comput,2017

5. Further stability analysis for delayed complex-valued recurrent neural networks

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