具有观测器的记忆神经网络状态估计

2022 14th International Conference on Advanced Computational Intelligence (ICACI) Pub Date : 2022-07-15 DOI:10.1109/icaci55529.2022.9837560

Moxuan Guo, Song Zhu

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引用次数: 0

摘要

这项工作探讨了考虑时变延迟和有界干扰的记忆神经网络(MNNs)的状态估计。通过实现指数稳定性，得到了代数判据的几个充分条件。建立由两个矩阵乘法定义的两类观测器，即Hadamard积和matl积，得到了使误差系统稳定的状态解估计。最后，通过数值模拟验证了所得结果的有效性。

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State Estimation for Memristive Neural Networks with Observer

This work explores state estimation considering Memristive Neural Networks (MNNs) with time-varying delays and bounded disturbances. Some sufficient conditions for algebraic criteria are derived from achieving exponential stability. Establishing two kinds of observers defined by two matrix multiplications, Hadamard product and matmul product, we obtain the estimation of state solutions such that the error system stability. Finally, the availability of the results is verified via a numerical simulation.

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来源期刊

2022 14th International Conference on Advanced Computational Intelligence (ICACI)

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