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Abstract: This Letter provides new exponential stability criteria for discrete-time neural networks with variable delays. The main technique is to reduce exponential convergence estimation of the neural network solution to that of one component of the corresponding solution by constructing Lyapunov function based on M-matrix. By introducing the tuning parameter diagonal matrix, the delay-independent and delay-dependent exponential stability conditions have been unified in the same mathematical formula. The effectiveness of the new results are illustrated by three examples. [Copyright &y& Elsevier]

Abstract: This Letter provides new exponential stability criteria for neural networks with variable delays. By applying the properties of M-matrix properties and inequality techniques, simple and improved delay-dependent exponential stability criteria are derived. These criteria extend and improve the existing ones, which is important in the design of neural networks. [Copyright &y& Elsevier]

Abstract: A wafer bending stage and a scanning probe microscope are combined to investigate the in situ domain pattern evolution in polycrystalline Bi3.25La0.75Ti3O12 films under stress. We observe the stress induced polarization reorientation that sensitively depends on the relative alignment of the BLT unit cell with respect to the stress. [Copyright &y& Elsevier]