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- W870869240 abstract "Abstract Inspired by fixed point theory, an iterative algorithm is proposed to identify bilinear models recursively in this paper. It is shown that the resulting iteration is a contraction mapping on a metric space when the number of input–output data points approaches infinity. This ensures the existence and uniqueness of a fixed point of the iterated function sequence and therefore the convergence of the iteration. As an application, one class of block-oriented systems represented by a cascade of a dynamic linear (L), a static nonlinear (N) and a dynamic linear (L) subsystems is illustrated. This gives a solution to the long-standing convergence problem of iteratively identifying LNL (Winer–Hammerstein) models. In addition, we extend the static nonlinear function (N) to a nonparametric model represented by using kernel machine." @default.
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- W870869240 date "2015-09-01" @default.
- W870869240 modified "2023-10-18" @default.
- W870869240 title "Fixed point iteration in identifying bilinear models" @default.
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- W870869240 doi "https://doi.org/10.1016/j.sysconle.2015.06.008" @default.
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