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PD研究員 ナラパン グナセカラン(NALLAPPAN, Gunasekaran / ナラパン グナセカラン)




学位 PhD  
生年月日 年齢 33歳
所属研究室 知能数理
研究分野 Artificial intelligence in games and Deep Learning for Natural Language Processing
最終学歴 Ph.D
職歴 Postdoc in Shibaura institute of technology, Japan (2018年10月01日~2020年09月30日)
Postdoc in Kunsan National University, South Korea (2017年05月01日~2018年09月30日)
主な研究論文 1. Gunasekaran, N., Zhai, G., & Yu, Q. (2020). Sampled-data synchronization of delayed multi-agent networks and its application to coupled circuit. Neurocomputing, 413, 499-511.

2. Gunasekaran, N., Thoiyab, N. M., Muruganantham, P., Rajchakit, G., & Unyong, B. (2020). Novel results on global robust stability analysis of dynamical delayed neural networks under parameter uncertainties. IEEE Access, 8, 178108-178116.

3. Gunasekaran, N., & Zhai, G. (2020). Sampled-data state-estimation of delayed complex-valued neural networks. International Journal of Systems Science, 51(2), 303-312.

4. Gunasekaran, N., & Joo, Y. H. (2019). Robust sampled-data fuzzy control for nonlinear systems and its applications: Free-weight matrix method. IEEE Transactions on Fuzzy Systems, 27(11), 2130-2139.

5. Gunasekaran, N., Saravanakumar, R., Joo, Y. H., & Kim, H. S. (2019). Finite-time synchronization of sampled-data T–S fuzzy complex dynamical networks subject to average dwell-time approach. Fuzzy Sets and Systems, 374, 40-59.
学会活動 Participated and Presented in the IEEE International Conference on Inventive Computation Technologies (ICICT), organized by RVS Technical campus, Coimbatore, Tamil Nadu, India, during 26 & 27 August 2016. Title: Sampled-data state estimation for delayed Markovian jump neural networks based on passive theory. N. Gunasekaran and M. Syed Ali.
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