MITS has secured NIRF India Ranking 2024 in the band 201 to 300.
Dr. Ramasamy Subramaniam

Qualification : Ph.D. (Gandhigram Rural Institute, Dindigul)

Designation : Asst. Professor

Details of Educational Qualification:

Course Specialization Group College Name/University Year of Passing
Ph.D. Mathematical Sciences Mathematical Sciences The Gandhigram Rural Institute- DeemedUniversity, Dindigu 2017
M.Phil. Mathematics M.Phil. Periyar University, Salem 2009
M.Sc. Mathematics M.Sc Mahendra Arts and Science College, Namakkal 2006
B.Sc. Mathematics B.Sc. Thiruvalluvar Government Arts College, Rasipuram 2003

 

 

My Publications

S.No Title of the Paper Full Details of Journal Name / Conference Name, Volume number, page number, Date
1 T-S fuzzy-based sliding mode control design for discrete-time nonlinear model and its applications. Information Sciences, DOI:https://doi.org/10.1016/j.ins.2020.01.010, I.F=5.524.
2 Robust exponential stability analysis for stochastic systems with actuator faults using improved weighted relaxed integral inequality. IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2019.2924327, I.F=7.351.
3 Robust extended dissipativity analysis for markovian jump discrete-time delayed stochastic singular neural networks. Neural Computing and Applications, DOI:10.1007/s00521-019-04497-y, I.F=4.664.
4 Passivity-based fuzzy ISMC for wind energy conversion systems with pmsg. IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2019.2930743, I.F=7.351.
5 Further results on dissipativity analysis for markovian jump neural networks with randomly occurring uncertainties and leakage delays. Neural Computing and Applications, 30(11), 3565–3579, I.F=4.664.
6 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(4), 717–735, I.F=4.664.
7 Dissipativity and passivity analysis for discrete-time complex-valued neural networks with leakage delay and probabilistic time-varying delays. International J ournal of Adaptive Control and Signal Processing, 31(6), 876–902, I.F=2.239.
8 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(3), 939–965, I.F=2.591.
9 Dissipativity and passivity analysis for discrete-time t–s fuzzy stochastic neural networks with leakage time-varying delays based on abel lemma approach. J ournal of the Franklin Institute, 353(14), 3313–3342, I.F=3.653.
10 Dissipativity and passivity analysis for uncertain discrete-time stochastic markovian jump neural networks with additive time-varying delays. Neurocomputing, 174, 795–805, I.F=3.317.
11 Stochastic dissipativity and passivity analysis for discrete-time neural networks with probabilistic time-varying delays in the leakage term. Applied Mathematics and Computation, 289, 237–257, I.F=3.092.
12 Robust dissipativity and passivity analysis for discrete-time stochastic neural networks with time-varying delay. Complexity, 21(3),47–58, I.F=2.591.
13 State estimation for discrete-time neural networks with two additive time-varying delay components based on passivity theory. Int J Pure Appl Math, 106(6), 131–141.
14 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, I.F=3.464.
15 Dissipativity and passivity analysis for discrete-time complex-valued neural networks with time-varying delay. Cogent Mathematics, 2(1), 1048580.
16 Passivity analysis for discrete-time neural networks with time-varying delay, International Conference on Nonlinear Dynamical Systems (ICNDS 2016), Department of Mathematics, Bharathiar University, India, 2016.
17 Passivity analysis for discrete-time Stochastic neural networks with time-delay, National Conference on Recent Developments in Di erential Equations and their Applications, Department of Mathematics, PSGR Krishnammal College for Women, India, 2016.
18 State estimation for discrete-time neural networks with two additive delays, National Conference on Mathematical Modelling and Fuzzy Logic Applications, Department of Mathematics, RVS Technical Campus, India, 2016.
19 Passivity analysis for discrete-time complex valued neural networks with distributed delay, National Seminar on Recent trends in Di erential Equations, Department of mathematics, Arulmigu Palaniandavar Arts College for Women, India, 2015.