Exponential passivity of memristive neural networks with time delays
Memristive neural networks are studied across many fields of science. To uncover their structural design principles, the paper introduces a general class of memristive neural networks with time delays. Passivity analysis is conducted by constructing suitable Lyapunov functional. The analysis in the...
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| Veröffentlicht in: | Neural networks 2014-01, Vol.49, p.11-18 |
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| container_title | Neural networks |
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| creator | Wu, Ailong Zeng, Zhigang |
| description | Memristive neural networks are studied across many fields of science. To uncover their structural design principles, the paper introduces a general class of memristive neural networks with time delays. Passivity analysis is conducted by constructing suitable Lyapunov functional. The analysis in the paper employs the results from the theories of nonsmooth analysis and linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and less conservatism of the proposed results. |
| doi_str_mv | 10.1016/j.neunet.2013.09.002 |
| format | Article |
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| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Algorithms Applied sciences Artificial intelligence Computer science control theory systems Computer Simulation Computers, Hybrid Connectionism. Neural networks Control system analysis Control theory. Systems Exact sciences and technology Exponential passivity Hybrid systems Linear Models Memory Memristive neural networks Neural Networks (Computer) Nonlinear Dynamics Time Factors |
| title | Exponential passivity of memristive neural networks with time delays |
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