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Multistability in a class of stochastic delayed Hopfield neural networks
Institution:1. Department of Mathematics, Middle East Technical University, 06531 Ankara, Turkey;2. Gazi University, Polatl? Faculty of Science and Arts, Department of Mathematics, 06900 Ankara, Turkey;3. Institute of Applied Mathematics, Middle East Technical University, 06531 Ankara, Turkey;1. College of Mathematics and Econometrics, Hunan University, Changsha 410082, China;2. Department of Electronic and Information Engineering, Bozhou University, Bozhou 236800, China;1. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China;2. School of Computer Science and Technology, Hubei PolyTechnic University, Huangshi 435003, China;3. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China;1. Department of Information Technology, Hunan Women’s University, Changsha, Hunan 410002, PR China;2. College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, PR China;3. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong;1. School of Mathematics, South China University of Technology, Guangzhou 510641, Guangdong, PR China;2. College of Mathematics and Information Science, Guangxi University, Nanning 530004, Guangxi, PR China;1. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Department of Electronics and Information Engineering, Southwest University, Chongqing 400715, China;2. Key Laboratory of Machine Perception and Children’s Intelligence Development, Chongqing University of Education, Chongqing, 400067, PR China;3. Department of Mathematics, Texas A&M University at Qatar, Doha, P.O. Box 23874, Qatar
Abstract:
Keywords:Stochastic Hopfield neural networks  Delay  Multistability  Mean square exponential stability  Positive invariant set  Lyapunov method
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