This paper is concerned with the filtering problem for a class of nonlinear systems with stochastic sensor saturations and Markovian measurement transmission delays, where the asymptotic stability in probability is considered. The sensors are subject to random saturations characterized by a Bernoulli distributed sequence. The transmission time-delays are governed by a discrete-time Markov chain with finite states. In the presence of the nonlinearities, stochastic sensor saturations and

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... time-delays, sufficient conditions are established to guarantee that the filtering process is asymptotically stable in probability without disturbances and also satisfies the H ∞ criterion with respect to nonzero exogenous disturbances under the zero-initial condition. Moreover, it is illustrated that the results can be specialized to linear filters. Two simulation examples are presented to show the effectiveness of the proposed algorithms.