| Analysis of Markovian jump stochastic Cohen–Grossberg BAM neural networks with time delays for exponential input-to-state stability T Radhika, A Chandrasekar, V Vijayakumar, Q Zhu Neural Processing Letters 55 (8), 11055-11072, 2023 | 67 | 2023 |
| Further results on input-to-state stability of stochastic Cohen–Grossberg BAM neural networks with probabilistic time-varying delays A Chandrasekar, T Radhika, Q Zhu Neural Processing Letters, 1-23, 2022 | 45 | 2022 |
| Input-to-state stability of stochastic Markovian jump genetic regulatory networks Y Cao, A Chandrasekar, T Radhika, V Vijayakumar Mathematics and Computers in Simulation 222, 174-187, 2024 | 40 | 2024 |
| An improved result on dissipativity and passivity analysis of Markovian jump stochastic neural networks with two delay components G Nagamani, T Radhika, Q Zhu IEEE Transactions on Neural Networks and Learning Systems 28 (12), 3018-3031, 2016 | 30 | 2016 |
| State estimation for genetic regulatory networks with two delay components by using second-order reciprocally convex approach A Chandrasekar, T Radhika, Q Zhu Neural Processing Letters, 1-19, 2022 | 28 | 2022 |
| Design of sampled data state estimator for Markovian jumping neural networks with leakage time-varying delays and discontinuous Lyapunov functional approach R Rakkiyappan, Q Zhu, T Radhika Nonlinear Dynamics 73, 1367-1383, 2013 | 28 | 2013 |
| Dissipativity and passivity analysis of Markovian jump neural networks with two additive time-varying delays G Nagamani, T Radhika Neural Processing Letters 44, 571-592, 2016 | 25 | 2016 |
| Dissipativity and passivity analysis of T–S fuzzy neural networks with probabilistic time-varying delays: a quadratic convex combination approach G Nagamani, T Radhika Nonlinear Dynamics 82, 1325-1341, 2015 | 20 | 2015 |
| A delay decomposition approach for robust dissipativity and passivity analysis of neutral‐type neural networks with leakage time‐varying delay G Nagamani, T Radhika, P Balasubramaniam Complexity 21 (5), 248-264, 2016 | 19 | 2016 |
| Delay-dependent dissipativity criteria for Markovian jump neural networks with random delays and incomplete transition probabilities G Nagamani, YH Joo, T Radhika Nonlinear Dynamics 91, 2503-2522, 2018 | 17 | 2018 |
| Improved event-triggered-based output tracking for a class of delayed networked T–S fuzzy systems MS Aslam, T Radhika, A Chandrasekar, Q Zhu International Journal of Fuzzy Systems, 1-14, 2024 | 14 | 2024 |
| Further results on dissipativity analysis for Markovian jump neural networks with randomly occurring uncertainties and leakage delays T Radhika, G Nagamani, Q Zhu, S Ramasamy, R Saravanakumar Neural Computing and Applications 30, 3565-3579, 2018 | 12 | 2018 |
| Dissipativity and passivity analysis of Markovian jump impulsive neural networks with time delays G Nagamani, T Radhika, P Gopalakrishnan International Journal of Computer Mathematics 94 (7), 1479-1500, 2017 | 11 | 2017 |
| A quadratic convex combination approach on robust dissipativity and passivity analysis for Takagi–Sugeno fuzzy Cohen–Grossberg neural networks with time‐varying delays G Nagamani, T Radhika Mathematical Methods in the Applied Sciences 39 (13), 3880-3896, 2016 | 11 | 2016 |
| Further results on dissipativity criterion for markovian jump discrete-time neural networks with two delay components via discrete wirtinger inequality approach S Ramasamy, G Nagamani, T Radhika Neural Processing Letters 45, 939-965, 2017 | 10 | 2017 |
| A note on approximate controllability of second-order impulsive stochastic Volterra-Fredholm integrodifferential system with infinite delay YK Ma, M Johnson, V Vijayakumar, T Radhika, A Shukla, KS Nisar Journal of King Saud University-Science 35 (4), 102637, 2023 | 6 | 2023 |
| Dissipativity analysis of stochastic memristor-based recurrent neural networks with discrete and distributed time-varying delays T Radhika, G Nagamani Network: Computation in Neural Systems 27 (4), 237-267, 2016 | 6 | 2016 |
| Finite-time H∞ synchronization of semi-Markov jump neural networks with two delay components with stochastic sampled-data control T Radhika, A Chandrasekar, V Vijayakumar Bulletin des Sciences Mathématiques 195, 103482, 2024 | | 2024 |
| Exponential State Estimation for Delayed Competitive Neural Network Via Stochastic Sampled-Data Control with Markov Jump Parameters Under Actuator Failure Y Cao, AR Subhashri, A Chandrasekar, T Radhika, K Przybyszewski Journal of Artificial Intelligence and Soft Computing Research 14 (4), 373-385, 2024 | | 2024 |
| Studies on extended passivity results for neural networks with time delays T Radhika Dindigul, 0 | | |
Nagamani GnaneswaranThe Gandhigram Rural Institute (Deemed to be University)Verified email at ruraluniv.ac.in
