~ Nonlinear Adaptive Filtering as a Form of Artificial Intelligence ~

The real life example 1

Identification of physical object code and data
This is an application for identification of the physical object. There are several sources with publicly available datasets. http://www.nonlinearbenchmark.org/ is one of them. This dataset is Wiener-Hammerstein System (2009).

The site has very detailed explanation of the object and how experimental data were collected. The recommended reference to data sources is also provided:

J. Schoukens, J. Suykens, L. Ljung. Wiener-Hammerstein Benchmark. 15th IFAC Symposium on System Identification (SYSID 2009), July 6-8, 2009, St. Malo, France.

The object is static nonlinearity sandwiched between two linear blocks. The length of sample is 188000 input/output pairs. It is recommended to use first half for training the model and second half for validation. The model is chosen as two sequential Urysohn blocks and identification is performed according to cascade article. Since the initial approximation is random the result is slightly different for each run of the program, but usually the error is near 1 percent.