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- W2616800511 abstract "This paper addresses the problem of finding the ideal perturbation signal to fully excite the dynamics of a non-linear system; in particular, an underwater vehicle. Two types of signal are considered; random noise and multi-level pseudorandom signals. They are applied to a previously identified model of an underwater vehicle and the data is used to train a radial basis function neural network. The network has a Non-linear AutoRegressive with eXogenous inputs (NARX) structure with the regressor size determined by a false nearest neighbours technique. The performance of the different signals are compared and evaluated." @default.
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- W2616800511 date "2003-09-01" @default.
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- W2616800511 title "A comparison of perturbation signals for mimo model-matching of underwater vehicles" @default.
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- W2616800511 doi "https://doi.org/10.1016/s1474-6670(17)37803-5" @default.
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