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In this paper, the state estimation problem is investigated for a class of discrete uncertain neural networks subject to time delays and missing measurements. Several mutually independent sets of Bernoulli-distributed white sequences are employed to describe the phenomena of randomly occurring uncertainties (ROUs) and missing measurements. We aim to design(More)
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