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Exponential stability criteria for linear neutral systems with applications to neural networks of neutral type. (English) Zbl 1506.93074

Summary: Linear neutral vector equations \[ \dot{x}(t)=A_0(t)\dot{x}(h_0(t))+\sum\limits_{k=1}^mA_k(t)x(h_k(t))+\int_{g(t)}^tP(t,s)x(s)ds \] are considered on interval \([0,\infty)\). Here \(x=(x_1,\dots,x_n)^T\), \(m\) is a positive integer, the entries of matrices \(A_l\), \(l=0,\dots,m,P\), and the delays \(h_k\), \(k=0,\dots,m,g\) are assumed to be Lebesgue measurable functions. New explicit criteria are derived on uniform exponential stability. Comparisons are made and discussed based on an overview of the existing results. An application is presented to local exponential stability of non-autonomous neural network models of neutral type.

MSC:

93D23 Exponential stability
93B70 Networked control
93C05 Linear systems in control theory
26A42 Integrals of Riemann, Stieltjes and Lebesgue type
Full Text: DOI

References:

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