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Multikernel Least Mean Square Algorithm
IEEE Transactions on Neural Networks and Learning Systems, 2014The multikernel least-mean-square algorithm is introduced for adaptive estimation of vector-valued nonlinear and nonstationary signals. This is achieved by mapping the multivariate input data to a Hilbert space of time-varying vector-valued functions, whose inner products (kernels) are combined in an online fashion.
Felipe A, Tobar +2 more
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Listing Expected Mean Square Components
Biometrics, 1965SUMMARY Methods for listing the components of the expected mean squares are presented for two classes of factorial experiments. The procedures are based upon the combinatorial technique aind a modification of the telescopic technique of completely nested classifications. The methods give the experimenter the freedom of finding the expected mean squares
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Root mean square error or mean absolute error? Use their ratio as well
Information Sciences, 2022exaly
Vibrational mean-square amplitude matrices
Journal of Molecular Spectroscopy, 1959openaire +1 more source