New Delay-Dependent Stability Criteria for Neural Networks With Time-Varying Delay

By Yong He, Guoping Liu, David Rees. IEEE Transactions on Neural Networks, 2007

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Stochastic Synchronization of Markovian Jump Neural Networks With Time-Varying Delay Using Sampled Data (2013, background): “(47) Inspired by the free-weighting matrix approach [9], we can find that, for any appropriately dimensioned matrix Hi, the following inequality holds:”
Stability Analysis for Neural Networks With Time-Varying Interval Delay (2007, methodology): “The comparison among Theorem 1 and Corollary 1 in this letter and those in [20], [21], [25], and [26] are listed in Table I for h 1 = 0.”
Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay (2010, methodology): “Specially, if , i.e., is constant, the upper bound is 1.4224 in [21], 1.9321 in [23], and 3.5841 in [ 25 ] and [26], respectively.”
A Delay System Method for Designing Event-Triggered Controllers of Networked Control Systems (2013, methodology): “Employing (21) and introducing some free matrices [7], by using a similar method to the proof in [25] except for the treatment of the , we can conclude that the system described by (17)–(19) is exponentially stable with an norm bound if (20) is satisfied.”
Synchronization and State Estimation for Discrete-Time Complex Networks With Distributed Delays (2008, background): “, [11] and [12], where the networks are deterministic and continuous time.”