Abstract
In this paper, the passivity is investigated for neural networks with time-varying delays of neutral type and generalized activation functions. By using Lyapunov method, Newton-Leibniz formulation and linear matrix inequality (LMI) technique, several delay-independent sufficient conditions in LMI are obtained to guarantee the passivity of the addressed neural networks. The proposed passivity criteria do not require the monotonicity of the activation functions and the differentiability of the time-varying delays, which means that our results generalize and further improve those in the earlier publications. An example is given to show the effectiveness and less conservatism of the obtained conditions.
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Wang, J., Song, Q. (2009). Passivity Analysis of Neural Networks with Time-Varying Delays of Neutral Type. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5551. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01507-6_62
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DOI: https://doi.org/10.1007/978-3-642-01507-6_62
Publisher Name: Springer, Berlin, Heidelberg
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