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- W1945900662 abstract "An identification method and a tracking controller for nonlinear discrete-time systems using the are proposed. The neural-gas network is a kind of self-organizing network, and was developed by Martinet and Schulten (1991). The system is identified by estimating a hypersurface in the space of input and output sequences using the neural-gas network. The metric of the space of the synapse weight is modified to increase efficiency of learning. The hypersurface is expressed with a method by means of rational Bezier surface or direct interpolation. An inverse model of the system is derived from the surface, which is applied to a tracking control problem." @default.
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- W1945900662 date "2002-12-24" @default.
- W1945900662 modified "2023-09-26" @default.
- W1945900662 title "Tracking control using self-organizing neural network" @default.
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- W1945900662 doi "https://doi.org/10.1109/cdc.1996.577243" @default.
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