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This paper investigates fusion filtering problems for time-delayed systems with multiple sensors of saturation nonlinearity, where process noise and measurement noise have unknown statistical characteristics but bounded energy. The internal asymptotic stability of the fusion error system in the absence of process noise and measurement noise is analyzed first. Then based on the Hinfin performance analysis of multi-sensor time-delayed fusion error systems, centralized and distributed fusion filters are designed to guarantee the asymptotic stability of the fusion error systems and to minimize the effect of the noise signals on the filtering error. The parameters of these filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities, which can be solved via efficient interior-point algorithms. A numerical example is given to demonstrate the effectiveness and applicability of the proposed designs.