Assistant Prof. Dr. G.Nagamani

 

Curriculum Vitae of Assistant Prof. Dr. G.Nagamani

Educational Qualifications Ph.D*, Mathematics awarded as Highly Commended Department of Mathematics The Gandhigram Rural University, 2009-2011 Dindigul. *Title of the Ph.D Thesis: Passivity Analysis of Neural Networks with Time-varying Delays M.Phil, Mathematics with First class Department of Mathematics Bharathiar University, Coimbatore, 1997-1999. M.Sc, Mathematics with First class Department of Mathematics Sri Sarada College for Women, Salem, 1995-1997. B.Sc, Mathematics with First class Department of Mathematics Sri Sarada College for Women, Salem, 1991-1994. Professional Experience  Served as Senior Lecturer in Mathematics at Mahendra Arts and Science College, Namakkal (DT), 05.06.2001 to 05.11.2008.  Worked as Senior Research Fellow under DST Project No. SR/S4/MS: 485/07, The Gandhigram Rural Institute (Deemed to be University), 10.11.2008 to 22.06.2011.  Serving as Assistant Professor in Mathematics, The Gandhigram Rural Institute (Deemed to be University), 22.06.2011 to till date Field of specialization Passivity Analysis, Neural Networks, Control Theory and Fractional Calculus. No. of Ph.D’s guided/guiding Ph.D’s Produced-2 / Ph.D’s Guiding – 4 Awards, Honors & Fellowships  Qualified CSIR-UGC Test for JRF and Eligibility for Lectureship (NET) in the year 2010 and secured 94/0178 rank.  Received Tamil Nadu Young Women Scientists Award 2012, instituted by Science City, Department of Higher Education, Government of Tamil Nadu.  Received Overseas Research Professor Fellowship and worked as Research Professor in Kunsan National University, Gunsan, Rep. of Korea for a period of one year from 01.12.2016 to 30.11.2017. Reviewer Activities: Acted as Reviewer for more than 22 journals in Elsevier, Springer, Taylors and Francis, Wiley Online Library, Inter science, IEEE Publishers. Papers presented in National/International Seminars/Conferences: 10 List of Publications in the Science Citation Indexed Journals with impact Factors: 1. G. Nagamani, T.Radhika, Further results on dissipativity analysis of stochastic memristor-based recurrent neural networks with discrete and distributed time-varying delay, Network: Computation in neural systems, Vol. 27, no. 4, pp. 237-267, 2016. (0.706). 2. Ramasamy, S., Nagamani, G., & Zhu, Q. Robust dissipativity and passivity analysis for discrete-time stochastic T–S fuzzy Cohen–Grossberg Markovian jump neural networks with mixed time delays. Nonlinear Dynamics, 85(4), 2777-2799, (2016). (4.339). 3. Nagamani.G, and S. Ramasamy. “Dissipativity and passivity analysis for discrete-time T–S fuzzy stochastic neural networks with leakage time-varying delays based on Abel lemma approach.” Journal of the Franklin Institute 353, no. 14 (2016): 33133342. (3.576). 4. Nagamani.G, Thirunavukkarasu Radhika, and Quanxin Zhu. “An improved result on dissipativity and passivity analysis of Markovian jump stochastic neural networks with two delay components.” IEEE transactions on neural networks and learning systems 28, no. 12 (2016): 3018-3031. (7.982). 5. Ramasamy, S., G. Nagamani, and P. Gopalakrishnan. “State estimation for discrete-time neural networks with two additive timevarying delay components based on passivity theory.” Int J Pure Appl Math 106, no. 6 (2016): 131-141.(0.325) . 6. Nagamani.G, and S. Ramasamy. “Stochastic dissipativity and passivity analysis for discrete-time neural networks with probabilistic time-varying delays in the leakage term.” Applied Mathematics and Computation 289 (2016): 237-257.(2.300). 7. Nagamani.G, Thirunavukkarasu Radhika, and Padmini Gopalakrishnan. “Dissipativity and passivity analysis of Markovian jump impulsive neural networks with time delays.” International Journal of Computer Mathematics 94, no. 7 (2017): 1479-1500. (1.054). 8. Nagamani. G., and T. Radhika. “A quadratic convex combination approach on robust dissipativity and passivity analysis for Takagi–Sugeno fuzzy Cohen–Grossberg neural networks with time‐varying delays.” Mathematical Methods in the Applied Sciences 39, no. 13 (2016): 3880-3896. (1.180). 9. Nagamani.G, S. Ramasamy, and Anke Meyer-Baese. “Robust dissipativity and passivity based state estimation for discrete-time stochastic Markov jump neural networks with discrete and distributed time-varying delays.” Neural Computing and Applications 28, no. 4 (2017): 717-735. (4.213). 10. Nagamani, G., and T. Radhika. “Dissipativity and passivity analysis of T–S fuzzy neural networks with probabilistic timevarying delays: a quadratic convex combination approach.” Nonlinear Dynamics 82, no. 3 (2015): 1325-1341.( 4.339). 11. Nagamani.G, and S. Ramasamy. “Dissipativity and passivity analysis for uncertain discrete-time stochastic Markovian jump neural networks with additive time-varying delays.” Neurocomputing 174 (2016): 795-805. (3.241). 12. Nagamani.G, and Thirunavukkarasu Radhika. “Dissipativity and passivity analysis of Markovian jump neural networks with two additive time-varying delays.” Neural Processing Letters 44, no. 2 (2016): 571-592.( 1.787).

13. Nagamani, G, Thirunavukkarasu Radhika, and Pagavathi Balasubramaniam. “A delay decomposition approach for robust dissipativity and passivity analysis of neutral‐type neural networks with leakage time‐varying delay.” Complexity 21, no. 5 (2016): 248-264. ( 1.829). 14. Nagamani. G, S. Ramasamy, and Pagavathigounder Balasubramaniam. “Robust dissipativity and passivity analysis for discrete‐time stochastic neural networks with time‐varying delay.” Complexity 21, no. 3 (2016): 47-58. ( 1.829). 15. Nagamani, G., and S. Ramasamy. “Dissipativity and passivity analysis for discrete-time complex-valued neural networks with time-varying delay.” Cogent Mathematics 2, no. 1 (2015): 1048580. 16. Vembarasan, V., G. Nagamani, P. Balasubramaniam, and Ju H. Park. “State estimation for delayed genetic regulatory networks based on passivity theory.” Mathematical biosciences 244, no. 2 (2013): 165-175. (1.5). 17. Lakshmanan, Shanmugam, Ju H. Park, D. H. Ji, H. Y. Jung, and G. Nagamani. “State estimation of neural networks with timevarying delays and Markovian jumping parameter based on passivity theory.” Nonlinear Dynamics 70, no. 2 (2012): 1421-1434. (4.339). 18. Balasubramaniam, Pagavathigounder, and Nagamani. G. “A delay decomposition approach to delay-dependent robust passive control for Takagi–Sugeno fuzzy nonlinear systems.” Circuits, Systems, and Signal Processing31, no. 4 (2012): 1319-1341. (1.998). 19. Nagamani,G., and P. Balasubramaniam. “Delay-dependent passivity criteria for uncertain switched neural networks of neutral type with interval time-varying delay.” Physica Scripta85, no. 4 (2012): 045010. (1.902). 20. Balasubramaniam, Pagavathigounder, and Nagamani.G. “Global robust passivity analysis for stochastic fuzzy interval neural networks with time-varying delays.” Expert Systems with Applications 39, no. 1 (2012): 732-742. (3.768). 21. Balasubramaniam, P., G. Nagamani, and R. Rakkiyappan. “Passivity analysis for neural networks of neutral type with Markovian jumping parameters and time delay in the leakage term.” Communications in Nonlinear Science and Numerical Simulation 16, no. 11 (2011): 4422-4437. ( 3.181). 22. Balasubramaniam, Pagavathigounder, and G. Nagamani. “A delay decomposition approach to delay-dependent passivity analysis for interval neural networks with time-varying delay.” Neurocomputing 74, no. 10 (2011): 1646-1653. (3.214). 23. Balasubramaniam, Pagavathigounder, and G. Nagamani. “Global robust passivity analysis for stochastic interval neural networks with interval time-varying delays and Markovian jumping parameters.” Journal of Optimization Theory and Applications 149, no. 1 (2011): 197-215. ( 1.234). 24. Nagamani, G., and P. Balasubramaniam. “Robust passivity analysis for Takagi–Sugeno fuzzy stochastic Cohen–Grossberg interval neural networks with time-varying delays.” Physica Scripta 83, no. 1 (2010): 015008. (1.902). 25. Balasubramaniam, P., and G. Nagamani. “Passivity analysis of neural networks with Markovian jumping parameters and interval time-varying delays.” Nonlinear Analysis: Hybrid Systems 4, no. 4 (2010): 853-864. (4.010). 26. Balasubramaniam, Pagavathigounder, G. Nagamani, and R. Rakkiyappan. “Global passivity analysis of interval neural networks with discrete and distributed delays of neutral type.” Neural Processing Letters 32, no. 2 (2010): 109-130. (1.787). 27. Balasubramaniam, P., and G. Nagamani. “Passivity analysis for uncertain stochastic neural networks with discrete interval and distributed time-varying delays.” Journal of Systems Engineering and Electronics 21, no. 4 (2010): 688-697. (0.572). 28. Ramasamy, S., and G. Nagamani. “Dissipativity and passivity analysis for discrete‐time complex‐valued neural networks with leakage delay and probabilistic time‐varying delays.” International Journal of Adaptive Control and Signal Processing 31, no. 6 (2017): 876-902. (2.082). 29. Ramasamy, S., G. Nagamani, and Thirunavukkarasu Radhika. “Further results on dissipativity criterion for Markovian jump discrete-time neural networks with two delay components via discrete Wirtinger inequality approach.” Neural Processing Letters 45, no. 3 (2017): 939-965. (1.787). 30. Radhika, Thirunavukkarasu, G. Nagamani, Quanxin Zhu, S. Ramasamy, and R. Saravanakumar. “Further results on dissipativity analysis for Markovian jump neural networks with randomly occurring uncertainties and leakage delays.” Neural Computing and Applications 30, no. 11 (2018): 3565-3579. (4.213). 31. Nagamani, G., Young Hoon Joo, and T. Radhika. “Delay-dependent dissipativity criteria for Markovian jump neural networks with random delays and incomplete transition probabilities.” Nonlinear Dynamics 91, no. 4 (2018): 2503-2522. (4.339). 32. Nagamani. G, Ganesan Soundararajan, and Quanxin Zhu. “Exponential State Estimation for Memristor-Based Discrete-Time BAM Neural Networks With Additive Delay Components.” IEEE transactions on cybernetics (2019). (8.803). 33. Joo, Young Hoon, and G. Nagamani. “Event-triggered stabilization for T–S fuzzysystems with asynchronous premise constraints and its application to wind turbine system.” IET Control Theory & Applications (2019). (3.296). 34. G. Nagamani, C. Karthik, S. Ramasamy and Quanxin Zhu, Robust exponential stability analysis for stochastic systems with actuator faults via new weighted relaxed integral inequalities, IEEE Transaction on Systems, Man and Cybernetics: Systems, http://dx.doi.org/10.1109/TSMC.2019.2924327. (5.131) 35. G. Nagamani, G. Soundararajan, S. Ramasamy, Muhammad Azeem, Robust extended dissipativity analysis for Markovian jump discrete-time delayed stochastic singular neural networks, Neural Computing and Applications, http://doi.org/10.1016/j.ins.2019.09.034. (4.213). 36. G. Nagamani, C. Karthik, G. Soundararajan, Observer-based exponential stabilization for time delay systems via new augmented weighted integral inequality, Journal of the Franklin Institute, https://doi.org/10.1016/j.jfranklin.2019.07.004 (3.576).
37. G. Nagamani, Young Hoon Joo, Han Sol Kim, A linear matrix inequality-based robust extended dissipativity criteria for uncertain systems with additive time-varying delays, IFAC Journal of Systems and Control (In press).