Exponential Synchronization of Inertial Memristor-Based Neural Networks with Time Delay Using Average Impulsive Interval Approach
This paper deals with the impulsive synchronization problem for a class of inertial memristor-based neural networks (IMNNs) with time delays by applying average impulsive interval approach. By adopting proper variable transformation, the original system can be converted into first-order differential...
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| Veröffentlicht in: | Neural processing letters 2019-12, Vol.50 (3), p.2053-2071 |
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| creator | Rakkiyappan, R. Gayathri, D. Velmurugan, G. Cao, Jinde |
| description | This paper deals with the impulsive synchronization problem for a class of inertial memristor-based neural networks (IMNNs) with time delays by applying average impulsive interval approach. By adopting proper variable transformation, the original system can be converted into first-order differential equations. By utilizing Lyapunov theory, theory of differential inclusion, Halanay inequality and average impulsive interval approach, we attain some adequate conditions that make sure the exponential synchronization of IMNNs under the impulsive control technique. Moreover some delay-dependent conditions for delayed impulsive synchronization of the considered system is obtained. Finally, numerical simulations are offered to exhibit the capacity of our theoretical findings. |
| doi_str_mv | 10.1007/s11063-019-09982-y |
| format | Article |
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By adopting proper variable transformation, the original system can be converted into first-order differential equations. By utilizing Lyapunov theory, theory of differential inclusion, Halanay inequality and average impulsive interval approach, we attain some adequate conditions that make sure the exponential synchronization of IMNNs under the impulsive control technique. Moreover some delay-dependent conditions for delayed impulsive synchronization of the considered system is obtained. Finally, numerical simulations are offered to exhibit the capacity of our theoretical findings.</description><subject>Artificial Intelligence</subject><subject>Complex Systems</subject><subject>Computational Intelligence</subject><subject>Computer Science</subject><subject>Differential equations</subject><subject>Investigations</subject><subject>Memristors</subject><subject>Neural networks</subject><subject>Signal processing</subject><subject>Synchronism</subject><subject>Time lag</subject><issn>1370-4621</issn><issn>1573-773X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kLtOAzEQRVcIJMLjB6gsURv82EdchhAgEoSCRKKzvN7ZxJDYi71JWDr-HEOQ6Kjmzsw9M9JNkjNKLighxWWglOQcEyowEaLPcLeX9GhWcFwU_Hk_al4QnOaMHiZHIbwQEjFGesnn6L1xFmxr1BI9dVYvvLPmQ7XGWeRqNLbgf3YPsPImtM7jKxWgQhNY-zieQLt1_jWgrWkXaGpWgK5hqTo0C8bO0WADXs0BjVfNehnMJirbgt9EctA03im9OEkOarUMcPpbj5PZzWg6vMP3j7fj4eAea05FiytdpUqQjPV1UUYNuUqZEBCbuhSs0GVZE1ExptOMk0LXvB-HlUjzLMu0Lvlxcr67G9--rSG08sWtvY0vJRO0z1OWMxJdbOfS3oXgoZaNNyvlO0mJ_I5a7qKWMWr5E7XsIsR3UIhmOwf_d_of6guFW4VD</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Rakkiyappan, R.</creator><creator>Gayathri, D.</creator><creator>Velmurugan, G.</creator><creator>Cao, Jinde</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope></search><sort><creationdate>20191201</creationdate><title>Exponential Synchronization of Inertial Memristor-Based Neural Networks with Time Delay Using Average Impulsive Interval Approach</title><author>Rakkiyappan, R. ; 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| subjects | Artificial Intelligence Complex Systems Computational Intelligence Computer Science Differential equations Investigations Memristors Neural networks Signal processing Synchronism Time lag |
| title | Exponential Synchronization of Inertial Memristor-Based Neural Networks with Time Delay Using Average Impulsive Interval Approach |
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