Finite time synchronization of memristor-based Cohen-Grossberg neural networks with mixed delays.

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Chuan Chen ; Lixiang Li ; Haipeng Peng ; Yixian Yang
  • Publisher: Public Library of Science (PLoS)
  • Journal: PLoS ONE, volume 12, issue 9 (issn: 1932-6203, eissn: 1932-6203)
  • Related identifiers: doi: 10.1371/journal.pone.0185007, pmc: PMC5607209
  • Subject: Computational Biology | Electronics | Research Article | Memory | Control Theory | Mathematics | Anatomy | Neural Networks | Electrical Engineering | Engineering and Technology | Computational Neuroscience | Artificial Intelligence | Physical Sciences | Control Engineering | Systems Science | Biology and Life Sciences | Computer and Information Sciences | Cognition | Materials Science | Neuroscience | Physiology | Medicine | Artificial Neural Networks | Q | Resistors | R | Capacitors | Nervous System | Synapses | Learning and Memory | Electrophysiology | Science | Materials by Attribute | Electrical Circuits | Medicine and Health Sciences | Neurophysiology | Cognitive Science

Finite time synchronization, which means synchronization can be achieved in a settling time, is desirable in some practical applications. However, most of the published results on finite time synchronization don’t include delays or only include discrete delays. In view ... View more
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