H ∞ state estimation of generalised neural networks with interval time-varying delays.

This paper focuses on studying theH∞state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov–Krasovskii functional are handled by the Jensen’s inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable withH∞performance. The proposed conditions are represented by linear matrix inequalities. OptimalH∞norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples. [ABSTRACT FROM PUBLISHER]