| Passivity analysis for neural networks of neutral type with Markovian jumping parameters and time delay in the leakage term P Balasubramaniam, G Nagamani, R Rakkiyappan Communications in Nonlinear Science and Numerical Simulation 16 (11), 4422-4437, 2011 | 93 | 2011 |
| State estimation of neural networks with time-varying delays and Markovian jumping parameter based on passivity theory S Lakshmanan, JH Park, DH Ji, HY Jung, G Nagamani Nonlinear Dynamics 70, 1421-1434, 2012 | 62 | 2012 |
| A delay decomposition approach to delay-dependent passivity analysis for interval neural networks with time-varying delay P Balasubramaniam, G Nagamani Neurocomputing 74 (10), 1646-1653, 2011 | 51 | 2011 |
| Robust event-triggered reliable control for TS fuzzy uncertain systems via weighted based inequality G Nagamani, YH Joo, G Soundararajan, R Mohajerpoor Information Sciences 512, 31-49, 2020 | 50 | 2020 |
| Passivity analysis of neural networks with Markovian jumping parameters and interval time-varying delays P Balasubramaniam, G Nagamani Nonlinear Analysis: Hybrid Systems 4 (4), 853-864, 2010 | 42 | 2010 |
| Robust dissipativity and passivity analysis for discrete-time stochastic T–S fuzzy Cohen–Grossberg Markovian jump neural networks with mixed time delays S Ramasamy, G Nagamani, Q Zhu Nonlinear Dynamics 85, 2777-2799, 2016 | 41 | 2016 |
| Global robust passivity analysis for stochastic fuzzy interval neural networks with time-varying delays P Balasubramaniam, G Nagamani Expert Systems with Applications 39 (1), 732-742, 2012 | 40 | 2012 |
| Robust dissipativity and passivity analysis for discrete‐time stochastic neural networks with time‐varying delay G Nagamani, S Ramasamy, P Balasubramaniam Complexity 21 (3), 47-58, 2016 | 35 | 2016 |
| Robust state estimation for fractional-order delayed BAM neural networks via LMI approach G Nagamani, M Shafiya, G Soundararajan, M Prakash Journal of the Franklin Institute 357 (8), 4964-4982, 2020 | 34 | 2020 |
| Exponential state estimation for memristor-based discrete-time BAM neural networks with additive delay components G Nagamani, GS Rajan, Q Zhu IEEE Transactions on Cybernetics 50 (10), 4281-4292, 2019 | 33 | 2019 |
| State estimation for delayed genetic regulatory networks based on passivity theory V Vembarasan, G Nagamani, P Balasubramaniam, JH Park Mathematical Biosciences 244 (2), 165-175, 2013 | 33 | 2013 |
| Event-triggered observer-based sliding mode control for TS fuzzy systems via improved relaxed-based integral inequality G Nagamani, C Karthik, YH Joo Journal of the Franklin Institute 357 (14), 9543-9567, 2020 | 32 | 2020 |
| Dissipativity and passivity analysis for discrete‐time complex‐valued neural networks with leakage delay and probabilistic time‐varying delays S Ramasamy, G Nagamani International Journal of Adaptive Control and Signal Processing 31 (6), 876-902, 2017 | 32 | 2017 |
| Global passivity analysis of interval neural networks with discrete and distributed delays of neutral type P Balasubramaniam, G Nagamani, R Rakkiyappan Neural Processing Letters 32 (2), 109-130, 2010 | 32 | 2010 |
| 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 |
| Dissipativity and passivity analysis for uncertain discrete-time stochastic Markovian jump neural networks with additive time-varying delays G Nagamani, S Ramasamy Neurocomputing 174, 795-805, 2016 | 30 | 2016 |
| Stochastic dissipativity and passivity analysis for discrete-time neural networks with probabilistic time-varying delays in the leakage term G Nagamani, S Ramasamy Applied Mathematics and Computation 289, 237-257, 2016 | 29 | 2016 |
| New finite-time passivity criteria for delayed fractional-order neural networks based on Lyapunov function approach M Shafiya, G Nagamani Chaos, Solitons & Fractals 158, 112005, 2022 | 27 | 2022 |
| 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 |
| Global synchronization of uncertain fractional-order BAM neural networks with time delay via improved fractional-order integral inequality M Shafiya, G Nagamani, D Dafik Mathematics and Computers in Simulation 191, 168-186, 2022 | 24 | 2022 |
P. BalasubramaniamThe Gandhigram Rural Institute-Deemed to be UniversityVerified email at ruraluniv.ac.in
