Abstract
This chapter is concerned with the problem of exponential passive filtering for a class of stochastic neutral-type neural networks with both semi-Markovian jump parameters and mixed time delays. Our aim is to estimate the state by a Luenberger-type observer such that the filter error dynamics are exponentially mean-square stable with an expected decay rate and an attenuation level. Sufficient conditions for existence of passive filters are obtained and a cone complementarity linearization procedure is employed to transform a nonconvex feasibility problem into a sequential minimization problem, which can be readily solved by existing optimization techniques.
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Li, F., Shi, P., Wu, L. (2017). Passive Filtering for Delayed Neutral-Type Semi-Markovian Jump Systems. In: Control and Filtering for Semi-Markovian Jump Systems. Studies in Systems, Decision and Control, vol 81. Springer, Cham. https://doi.org/10.1007/978-3-319-47199-0_6
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DOI: https://doi.org/10.1007/978-3-319-47199-0_6
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