Novel lemmas enhance settling time estimation in complex-valued neural networks, suggesting improved synchronization methods.
The core contribution of this article is the development of two novel fixed‐time (FXT) stability lemmas, which eliminate the need for conventional case‐based discussions on and . To validate the proposed lemmas, the FXT synchronization problem of discontinuous fuzzy complex‐valued inertial neural networks (DFCVINNs) is investigated using a nonseparation approach combined with elementary inequality techniques. In comparison with existing results, the proposed method significantly enhances the accuracy of settling time (ST) estimation. Finally, numerical simulations are presented to demonstrate the effectiveness and correctness of the theoretical findings.
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Zhou et al. (2026) studied this question.
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