Global dissipativity of delayed discrete-time inertial neural networks

Stabilization for a class of delayed switched inertial neural networks via non-reduced order method

“…The transformation idea of (21) has been frequently adopted in existing works (Chen et al, 2020; Kumar and Das, 2020; Li et al, 2020; Tang and Jian, 2018; Tu et al, 2016, 2017; Zhou and Yao, 2018). In this way, the selectable scalar μ is critical in the main results of these above works, with which whether the criteria hold are closely associated.…”

“…In Li et al (2020), stability and synchronization control for INN were discussed by means of linear transformation with both matrix measure method and Lyapunov strategy. In Chen et al (2020), global dissipativity for discrete-time INN was investigated by variable substitution and the generalized matrix-measure concept. In most of the above works, the second-order INN is reduced to the first-order network on the basis of a linear transformation, it is called reduced-order method.…”

“…Also, two particular classes of global stabilization issue including global asymptotic stabilization and global exponential stabilization for the considered SINN are discussed. The main innovations of this paper include: (i) Different from the stability analysis and stabilization study of conventional INN provided in the literature (Chen et al, 2020;Kumar and Das, 2020;Li et al, 2020;Tang and Jian, 2018;Tu et al, 2016Tu et al, , 2017Zhou and Yao, 2018), we consider a special class of delayed INN with state-dependent switched. (ii) Different from employing a linear transformation, we address two particular classes of global stabilization issue for the considered second-order SINN directly via non-reduced order means; (iii) Compared with some existing work, our presented approach is more effective, which is shown by a comparison study.…”

Analysis of Hopf–Hopf Interactions Induced by Multiple Delays for Inertial Hopfield Neural Models

“…The authors considered complex codimension-two bifurcations and coexistence dynamics for delayed neural networks with inertia terms [20][21][22][23][24][25][26]. The criteria for global synchronization and dissipativity are established on inertial neural networks with discrete-time or time-varying delays [27][28][29][30].…”

Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks

“…In many scenarios, it has been demonstrated that DSs outperform continuous systems. As a result, the theory of DSs holds significant importance; please refer to references [30][31][32][33][34][35][36][37][38]. Reports [35][36][37][38] have explored various types of discrete INNs.…”