A new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networks

In this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield neural networks is given in terms of a linear matrix inequality, which is less conservative than existing ones in the literature. This condition guarantees the existence of a unique equilibrium point and its global asymptotic stability of a given delayed Hopfield neural network. Examples are provided to show the reduced conservatism of the proposed condition. © 2006 IEEE.published_or_final_versio

A new criterion of delay-dependent asymptotic stability for Hopfield neural networks with time delay

In this brief, the problem of global asymptotic stability for delayed Hopfield neural networks (HNNs) is investigated. A new criterion of asymptotic stability is derived by introducing a new kind of Lyapunov-Krasovskii functional and is formulated in terms of a linear matrix inequality (LMI), which can be readily solved via standard software. This new criterion based on a delay fractioning approach proves to be much less conservative and the conservatism could be notably reduced by thinning the delay fractioning. An example is provided to show the effectiveness and the advantage of the proposed result. © 2008 IEEE.published_or_final_versio

Stability analysis of discrete-time recurrent neural networks with stochastic delay

This paper is concerned with the stability analysis of discrete-time recurrent neural networks (RNNs) with time delays as random variables drawn from some probability distribution. By introducing the variation probability of the time delay, a common delayed discrete-time RNN system is transformed into one with stochastic parameters. Improved conditions for the mean square stability of these systems are obtained by employing new Lyapunov functions and novel techniques are used to achieve delay dependence. The merit of the proposed conditions lies in its reduced conservatism, which is made possible by considering not only the range of the time delays, but also the variation probability distribution. A numerical example is provided to show the advantages of the proposed conditions. © 2009 IEEE.published_or_final_versio

Інтелектуальні системи діагностики теплового стану електродвигуна: монографія.

Розглядаються теоретичні і практичні питання теплової діагностики електродвигунів для рухомого складу електротранспорту. У монографії проведено теоретичні дослідження і наведено математичний апарат, що обґрунтовує застосування нових систем діагностики електродвигунів на основі нейронних мереж. Монографія призначена для фахівців проектних, транспортних і комунальних організацій міського господарства, а також буде корисною викладацькому складу, аспірантам і студентам технічних спеціальностей