Shi, P.Li, F.Wu, L.Lim, C.2017-10-262017-10-262017IEEE Transactions on Neural Networks and Learning Systems, 2017; 28(9):2101-21142162-237X2162-2388http://hdl.handle.net/2440/109077This paper investigates 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 states by designing a Luenberger-type observer, such that the filter error dynamics are mean-square exponentially stable with an expected decay rate and an attenuation level. Sufficient conditions for the existence of passive filters are obtained, and a convex optimization algorithm for the filter design is given. In addition, a cone complementarity linearization procedure is employed to cast the nonconvex feasibility problem into a sequential minimization problem, which can be readily solved by the existing optimization techniques. Numerical examples are given to demonstrate the effectiveness of the proposed techniques.en© 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.Filtering; neural networks (NNs); semi-Markovian jump systems (S-MJSs); time delayJournal article003005001810.1109/TNNLS.2016.25738530004077615000102-s2.0-84974856554255289Shi, P. [0000-0001-6295-0405] [0000-0001-8218-586X] [0000-0002-0864-552X] [0000-0002-1358-2367] [0000-0002-5312-5435]Lim, C. [0000-0002-2463-9760]