The quantized kernel recursive least squares (QKRLS) is a model proposed by Chen et al. [1].
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QKRLS is the QKRLS model.
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GridSearch_AllDatasets is the file to perform a grid search for all datasets and store the best hyper-parameters.
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Runtime_AllDatasets perform 30 simulations for each dataset and compute the mean runtime and the standard deviation.
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MackeyGlass is the script to prepare the Mackey-Glass time series, perform simulations, compute the results and plot the graphics.
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Nonlinear is the script to prepare the nonlinear dynamic system identification time series, perform simulations, compute the results and plot the graphics.
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LorenzAttractor is the script to prepare the Lorenz Attractor time series, perform simulations, compute the results and plot the graphics.
[1] B. Chen, S. Zhao, P. Zhu, J. C. Principe, Quantized kernel recursive least squares algorithm, IEEE Transactions on Neural Networks and Learning Systems 24 (9) (2013) 1484–1491. doi:https://doi.org/10.1109/TNNLS.952013.2258936