Journal
MODERN PHYSICS LETTERS B
Volume 32, Issue 3, Pages -Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0217984918500288
Keywords
BAM memristive neural networks; multiple proportional delays; anti synchronization
Funding
- National Key Research and Development Program of China [2017YFB0702300]
- China Scholarship Council (CSC)
- National Natural Science Foundation of China [61603032, 61174103]
- National Key Technologies R&D Program of China [2015BAK38B01]
- Fundamental Research Funds for the Central Universities [06500025]
- University of Science and Technology Beijing National Taipei University of Technology Joint Research Program [TW201705]
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Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.
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