Input-output data sets for development and benchmarking in nonlinear identification
نویسنده
چکیده
This report presents two sets of data, suitable for development, testing and benchmarking of system identification algorithms for nonlinear processes. The first data set is recorded from a laboratory process that can be well described by a block oriented nonlinear model. The data set is challenging; it consists of only 500 samples, the nonlinear effect is large and the damping is not too good. The second data set is recorded from a laboratory process known to be governed by nonlinear differential equations.
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تاریخ انتشار 2010