Global Passivity Analysis of Interval Neural Networks with Discrete and Distributed Delays of Neutral Type. - Pagavathigounder Balasubramaniam; Gnaneswaran Nagamani; R. Rakkiyappan (Neural Process. Lett., 2010)

A delay decomposition approach to delay-dependent passivity analysis for interval neural networks with time-varying delay. - Pagavathigounder Balasubramaniam; Gnaneswaran Nagamani (Neurocomputing, 2011)

Global Robust Passivity Analysis for Stochastic Interval Neural Networks with Interval Time-Varying Delays and Markovian Jumping Parameters. - Pagavathigounder Balasubramaniam; Gnaneswaran Nagamani (J. Optim. Theory Appl., 2011)

A Delay Decomposition Approach to Delay-Dependent Robust Passive Control for Takagi-Sugeno Fuzzy Nonlinear Systems. - Pagavathigounder Balasubramaniam; Gnaneswaran Nagamani (Circuits Syst. Signal Process., 2012)

Global robust passivity analysis for stochastic fuzzy interval neural networks with time-varying delays. - Pagavathigounder Balasubramaniam; Gnaneswaran Nagamani (Expert Syst. Appl., 2012)

Stochastic dissipativity and passivity analysis for discrete-time neural networks with probabilistic time-varying delays in the leakage term. - Gnaneswaran Nagamani; S. Ramasamy (Appl. Math. Comput., 2016)

Robust dissipativity and passivity analysis for discrete-time stochastic neural networks with time-varying delay. - Gnaneswaran Nagamani; S. Ramasamy; Pagavathigounder Balasubramaniam (Complex., 2016)

A delay decomposition approach for robust dissipativity and passivity analysis of neutral-type neural networks with leakage time-varying delay. - Gnaneswaran Nagamani; Thirunavukkarasu Radhika; Pagavathi Balasubramaniam (Complex., 2016)

Dissipativity and passivity analysis for uncertain discrete-time stochastic Markovian jump neural networks with additive time-varying delays. - Gnaneswaran Nagamani; S. Ramasamy (Neurocomputing, 2016)

Dissipativity and passivity analysis for discrete-time T-S fuzzy stochastic neural networks with leakage time-varying delays based on Abel lemma approach. - Gnaneswaran Nagamani; S. Ramasamy (J. Frankl. Inst., 2016)

Dissipativity and Passivity Analysis of Markovian Jump Neural Networks with Two Additive Time-Varying Delays. - Gnaneswaran Nagamani; Thirunavukkarasu Radhika (Neural Process. Lett., 2016)

Dissipativity and passivity analysis of Markovian jump impulsive neural networks with time delays. - Gnaneswaran Nagamani; Thirunavukkarasu Radhika; Padmini Gopalakrishnan (Int. J. Comput. Math., 2017)

Robust dissipativity and passivity based state estimation for discrete-time stochastic Markov jump neural networks with discrete and distributed time-varying delays. - Gnaneswaran Nagamani; S. Ramasamy; Anke Meyer-Baese (Neural Comput. Appl., 2017)

Further Results on Dissipativity Criterion for Markovian Jump Discrete-Time Neural Networks with Two Delay Components Via Discrete Wirtinger Inequality Approach. - S. Ramasamy; Gnaneswaran Nagamani; Thirunavukkarasu Radhika (Neural Process. Lett., 2017)

An Improved Result on Dissipativity and Passivity Analysis of Markovian Jump Stochastic Neural Networks With Two Delay Components. - Gnaneswaran Nagamani; Thirunavukkarasu Radhika; Quanxin Zhu (IEEE Trans. Neural Networks Learn. Syst., 2017)

Further results on dissipativity analysis for Markovian jump neural networks with randomly occurring uncertainties and leakage delays. - Thirunavukkarasu Radhika; Gnaneswaran Nagamani; Quanxin Zhu; S. Ramasamy; R. Saravanakumar 001 (Neural Comput. Appl., 2018)

A linear matrix inequality-based extended dissipativity criteria for linear systems with additive time-varying delays. - Gnaneswaran Nagamani; Young Hoon Joo; Han Sol Kim (IFAC J. Syst. Control., 2019)

Observer-based exponential stabilization for time-delay systems via augmented weighted integral inequality. - Gnaneswaran Nagamani; C. Karthik; G. Soundararajan (J. Frankl. Inst., 2019)

Robust event-triggered reliable control for T-S fuzzy uncertain systems via weighted based inequality. - Gnaneswaran Nagamani; Young Hoon Joo; G. Soundararajan; Reza Mohajerpoor (Inf. Sci., 2020)

Event-triggered observer-based sliding mode control for T-S fuzzy systems via improved relaxed-based integral inequality. - Gnaneswaran Nagamani; C. Karthik; Young Hoon Joo (J. Frankl. Inst., 2020)

Robust state estimation for fractional-order delayed BAM neural networks via LMI approach. - Gnaneswaran Nagamani; M. Shafiya; G. Soundararajan; Mani Prakash (J. Frankl. Inst., 2020)

Robust extended dissipativity analysis for Markovian jump discrete-time delayed stochastic singular neural networks. - Gnaneswaran Nagamani; G. Soundararajan; Ramasamy Subramaniam; Muhammad Azeem (Neural Comput. Appl., 2020)

An LMI Based State Estimation for Fractional-Order Memristive Neural Networks with Leakage and Time Delays. - Gnaneswaran Nagamani; M. Shafiya; G. Soundararajan (Neural Process. Lett., 2020)

Exponential State Estimation for Memristor-Based Discrete-Time BAM Neural Networks With Additive Delay Components. - Gnaneswaran Nagamani; Ganesan Soundara Rajan; Quanxin Zhu (IEEE Trans. Cybern., 2020)

State-Feedback Filtering for Delayed Discrete-Time Complex-Valued Neural Networks. - Ganesan Soundara Rajan; Gnaneswaran Nagamani (IEEE Trans. Neural Networks Learn. Syst., 2020)

Delay-Dependent and Independent State Estimation for BAM Cellular Neural Networks with Multi-Proportional Delays. - Gnaneswaran Nagamani; A. Karnan; G. Soundararajan (Circuits Syst. Signal Process., 2021)

Robust Exponential Stability Analysis for Stochastic Systems With Actuator Faults Using Improved Weighted Relaxed Integral Inequality. - Gnaneswaran Nagamani; Karthik Chinnasamy; Ramasamy Subramaniam; Quanxin Zhu (IEEE Trans. Syst. Man Cybern. Syst., 2021)

Exponential extended dissipative performance for delayed discrete-time neural networks under memoryless resilient-based observer design. - B. Adhira; Gnaneswaran Nagamani; G. Soundararajan (J. Frankl. Inst., 2022)

Non-fragile state estimation for memristive cellular neural networks with proportional delay. - A. Karnan; Gnaneswaran Nagamani (Math. Comput. Simul., 2022)

Global synchronization of uncertain fractional-order BAM neural networks with time delay via improved fractional-order integral inequality. - M. Shafiya; Gnaneswaran Nagamani; Dafik (Math. Comput. Simul., 2022)

Robust stabilization of T-S fuzzy systems via improved integral inequality. - Karthik Chinnasamy; Gnaneswaran Nagamani; Ramasamy Subramaniyam; Dafik (Soft Comput., 2022)

Extended dissipativity criterion for fractional-order neural networks with time-varying parameter and interval uncertainties. - M. Shafiya; Gnaneswaran Nagamani (Comput. Appl. Math., 2022)

Non-fragile extended dissipative synchronization control of delayed uncertain discrete-time neural networks. - B. Adhira; Gnaneswaran Nagamani; Dafik (Commun. Nonlinear Sci. Numer. Simul., 2023)

Synchronization of Uncertain Neural Networks with Additive Time-Varying Delays and General Activation Function. - A. Karnan; Gnaneswaran Nagamani (Neural Process. Lett., 2023)

Non-fragile output-feedback synchronization for delayed discrete-time complex-valued neural networks with randomly occurring uncertainties. - G. Soundararajan; Gnaneswaran Nagamani (Neural Networks, 2023)

Extended Dissipativity Performance for the Delayed Discrete-Time Neural Networks with Observer-Based Control. - B. Adhira; Gnaneswaran Nagamani (Neural Process. Lett., 2023)

Exponential H∞ synchronization and anti-synchronization of delayed discrete-time complex-valued neural networks with uncertainties. - K. Sri Raja Priyanka; G. Soundararajan; Ardak Kashkynbayev; Gnaneswaran Nagamani (Math. Comput. Simul., 2023)

Non-fragile projective synchronization of delayed discrete-time neural networks via generalized weighted summation inequality. - K. Sri Raja Priyanka; Gnaneswaran Nagamani (Appl. Math. Comput., 2024)

Exponential H∞ filtering for complex-valued uncertain discrete-time neural networks with time-varying delays. - G. Soundararajan; Gnaneswaran Nagamani; Ardak Kashkynbayev (Commun. Nonlinear Sci. Numer. Simul., 2024)

Co-existence of robust output-feedback synchronization and anti-synchronization of delayed discrete-time neural networks with its application. - K. Sri Raja Priyanka; G. Soundararajan; Ardak Kashkynbayev; Gnaneswaran Nagamani (Comput. Appl. Math., 2024)

Extended dissipative criteria for delayed semi-discretized competitive neural networks. - B. Adhira; Gnaneswaran Nagamani (Neural Process. Lett., 2024)

Region bounded observer design for T-S fuzzy systems with nonlinear perturbations. - R. Elavarasi; Gnaneswaran Nagamani (Commun. Nonlinear Sci. Numer. Simul., 2025)

Extended dissipativity analysis of semi-discretized multi-delayed memristive Cohen-Grossberg neural networks via non-fragile synchronization approach. - B. Adhira; Santo Banerjee; Gnaneswaran Nagamani (J. Frankl. Inst., 2025)

Extended dissipativity-based finite-time contractive boundedness for delayed discrete-time neural networks via event-triggered approach. - B. Adhira; Gnaneswaran Nagamani (Neural Comput. Appl., 2025)

Scalar projective synchronization for uncertain T-S fuzzy systems with unified control fluctuation: Implementation to quadruple-tank process model. - R. Elavarasi; B. Adhira; Gnaneswaran Nagamani; Van Thanh Huynh (Expert Syst. Appl., 2026)