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A. Chandrasekar 0001
Person information
- affiliation: Bharathiar University, Department of Mathematics, Coimbatore, India
Other persons with the same name
- A. Chandrasekar 0002
(aka: Arumugam Chandrasekar 0002) — St. Josephs College of Engineering, Department of Computer Science and Engineering, Chennai, India
- A. Chandrasekar 0003 — Indian Institute of Space Science and Technology Thiruvananthapuram, India
- A. Chandrasekar 0004 — Indian Council of Agricultural Research, National Research Centre for Banana, Tiruchirapalli, India
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2020 – today
- 2024
- [j21]Muhammad Shamrooz Aslam, Thirunavukkarasu Radhika, Arunachalam Chandrasekar, Quanxin Zhu:
Improved Event-Triggered-Based Output Tracking for a Class of Delayed Networked T-S Fuzzy Systems. Int. J. Fuzzy Syst. 26(4): 1247-1260 (2024) - [j20]Yang Cao, Subhashri Alwarappan Ravisankar, A. Chandrasekar, Thirunavukkarasu Radhika, Krzysztof Przybyszewski:
Exponential State Estimation for Delayed Competitive Neural Network Via Stochastic Sampled-Data Control with Markov Jump Parameters Under Actuator Failure. J. Artif. Intell. Soft Comput. Res. 14(4): 373-385 (2024) - [j19]Yang Cao
, A. Chandrasekar, Thirunavukkarasu Radhika, V. Vijayakumar
:
Input-to-state stability of stochastic Markovian jump genetic regulatory networks. Math. Comput. Simul. 222: 174-187 (2024) - 2023
- [j18]Thirunavukkarasu Radhika, A. Chandrasekar, V. Vijayakumar, Quanxin Zhu:
Analysis of Markovian Jump Stochastic Cohen-Grossberg BAM Neural Networks with Time Delays for Exponential Input-to-State Stability. Neural Process. Lett. 55(8): 11055-11072 (2023) - 2022
- [j17]A. Chandrasekar, Thirunavukkarasu Radhika
, Quanxin Zhu
:
State Estimation for Genetic Regulatory Networks with Two Delay Components by Using Second-Order Reciprocally Convex Approach. Neural Process. Lett. 54(1): 327-345 (2022) - [j16]A. Chandrasekar, Thirunavukkarasu Radhika
, Quanxin Zhu:
Further Results on Input-to-State Stability of Stochastic Cohen-Grossberg BAM Neural Networks with Probabilistic Time-Varying Delays. Neural Process. Lett. 54(1): 613-635 (2022)
2010 – 2019
- 2016
- [j15]Chandrasekar Pradeep
, Arunachalam Chandrasekar, Rangasamy Murugesu, Rajan Rakkiyappan:
Robust stability analysis of stochastic neural networks with Markovian jumping parameters and probabilistic time-varying delays. Complex. 21(5): 59-72 (2016) - [j14]A. Chandrasekar, R. Rakkiyappan:
Impulsive controller design for exponential synchronization of delayed stochastic memristor-based recurrent neural networks. Neurocomputing 173: 1348-1355 (2016) - [j13]A. Chandrasekar, R. Rakkiyappan, Xiaodi Li:
Effects of bounded and unbounded leakage time-varying delays in memristor-based recurrent neural networks with different memductance functions. Neurocomputing 202: 67-83 (2016) - [j12]R. Rakkiyappan, E. Udhaya Kumari, A. Chandrasekar, Ramasamy Krishnasamy:
Synchronization and periodicity of coupled inertial memristive neural networks with supremums. Neurocomputing 214: 739-749 (2016) - [j11]R. Rakkiyappan, A. Chandrasekar, S. Lakshmanan:
Stochastic sampled data robust stabilisation of T-S fuzzy neutral systems with randomly occurring uncertainties and time-varying delays. Int. J. Syst. Sci. 47(10): 2247-2263 (2016) - 2015
- [j10]R. Rakkiyappan, A. Chandrasekar, Shanmugam Lakshmanan
, Ju H. Park:
Exponential stability for markovian jumping stochastic BAM neural networks with mode-dependent probabilistic time-varying delays and impulse control. Complex. 20(3): 39-65 (2015) - [j9]A. Chandrasekar, R. Rakkiyappan, Jinde Cao
:
Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. Neural Networks 70: 27-38 (2015) - [j8]Rajan Rakkiyappan, A. Chandrasekar, Jinde Cao:
Passivity and Passification of Memristor-Based Recurrent Neural Networks With Additive Time-Varying Delays. IEEE Trans. Neural Networks Learn. Syst. 26(9): 2043-2057 (2015) - 2014
- [j7]R. Rakkiyappan, A. Chandrasekar, Shanmugam Lakshmanan, Ju H. Park:
State estimation of memristor-based recurrent neural networks with time-varying delays based on passivity theory. Complex. 19(4): 32-43 (2014) - [j6]R. Rakkiyappan, A. Chandrasekar, Shanmugam Lakshmanan
, Ju H. Park
:
Exponential stability of Markovian jumping stochastic Cohen-Grossberg neural networks with mode-dependent probabilistic time-varying delays and impulses. Neurocomputing 131: 265-277 (2014) - [j5]A. Chandrasekar, R. Rakkiyappan, Fathalla A. Rihan
, Shanmugam Lakshmanan
:
Exponential synchronization of Markovian jumping neural networks with partly unknown transition probabilities via stochastic sampled-data control. Neurocomputing 133: 385-398 (2014) - [j4]Quanxin Zhu, R. Rakkiyappan, A. Chandrasekar:
Stochastic stability of Markovian jump BAM neural networks with leakage delays and impulse control. Neurocomputing 136: 136-151 (2014) - [j3]R. Rakkiyappan, Quanxin Zhu, A. Chandrasekar:
Stability of stochastic neural networks of neutral type with Markovian jumping parameters: A delay-fractioning approach. J. Frankl. Inst. 351(3): 1553-1570 (2014) - [j2]A. Chandrasekar, R. Rakkiyappan, Jinde Cao
, Shanmugam Lakshmanan
:
Synchronization of memristor-based recurrent neural networks with two delay components based on second-order reciprocally convex approach. Neural Networks 57: 79-93 (2014) - 2013
- [j1]R. Rakkiyappan, A. Chandrasekar, Shanmugam Lakshmanan
, Ju H. Park, Ho Y. Jung:
Effects of leakage time-varying delays in Markovian jump neural networks with impulse control. Neurocomputing 121: 365-378 (2013)
Coauthor Index
aka: Rajan Rakkiyappan
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last updated on 2024-08-11 00:11 CEST by the dblp team
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