Abstract
In the paper an approach to Hammerstein system identification based on quantized low-power observations is presented. In the presented approach realisations of discrete-time multisine random processes are used as the Hammerstein system excitation and the overall Hammerstein system identification problem is decomposed into the linear dynamic control channel subsystem, the corresponding disturbance at linear dynamic control channel subsystem output and input memoryless nonlinearity identification problems. The presented discussion is illustrated by a simulation example showing properties of the presented approach.
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