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Examines global exponential stability in neutral-type networks, indicating novel solutions.
This paper presents an analysis of neutral-type delayed inertial neural networks (NDINNs) by using the characteristic method. The study introduces three novel sufficient conditions for the global exponential stability of NDINNs, formulated as a series of linear scalar inequalities. This approach sets them apart from previous results and facilitates straightforward solutions. The theoretical findings are validated through three numerical examples, each accompanied by relevant simulations.
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Chen et al. (2026) studied this question.
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