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Home / Journals / Applied and Computational Mathematics / Recurrent neural networks, Bifurcation Analysis and Control Theory of Complex Systems
Recurrent neural networks, Bifurcation Analysis and Control Theory of Complex Systems
Lead Guest Editor:
Dr. Adnène Arbi
Laboratory of Engineering Mathematics (LR01ES13), Tunisia Polytechnic School, University of Carthage, Bizerta, Tunisia
Guest Editors
Nitin Shelke
Department of Computer Science & Engineering, G. H. Raisoni college of Engineering and Management
Amravati, Maharashtra, India
Hamed Daei Kasmaei
Department of Mathematics and Statistics, Central Tehran Branch, Islamic Azad University
Tehran, Iran
Zhinan Xia
Department of Applied Mathematics, Zhejiang University of Technology
Hangzhou, Zhejiang, China
Mehdi Fallah
Renewable Energy Research Center (RERC), Faculty of Electrical Engineering, Sahand University of Technology
Tabriz, East Azerbayjan, Iran
Yinyan Zhang
Department of Computing, The Hong Kong Polytechnic University
Hum Hom, Kowloon, Hong Kong
Aydin Azizi
Department of engineering, German University of Technology
Muscat, Oman
Paper List
Authors: Aydin Azizi, Niloofar Malekzadeh Fard, Hamed Mobki, Adnène Arbi
Pages: 1-11 Published Online: Jul. 11, 2017
DOI: 10.11648/j.acm.s.2018070102.11
Views 306 Downloads 26
Authors: Pabel Shahrear, Amit Kumar Chakraborty, Md. Anowarul Islam, Ummey Habiba
Pages: 12-21 Published Online: Sep. 6, 2017
DOI: 10.11648/j.acm.s.2018070102.12
Views 211 Downloads 28
In the last few years, several systems of neural networks have been investigated in nonlinear systems theory and have had a huge impact on the scientist research. Due to their complexities in the design, analysis, and control, innovative ideas, novel models, and techniques are still expected in the future in these expanding areas.

This special issue is intended to present and discuss modeling in recurrent neural networks and their complexity in the nonlinear systems theory. It is expected that novel complex models, their bifurcation analysis, and their related control techniques will be established. Among others, applications in pattern recognition, optimization, cryptography and biosciences disciplines are especially encouraged to be submitted to this special issue to present their related latest developments.
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