Abstract
A k-order Recursive Quadratic learning algorithm is proposed and its features are described in detail in this paper. Simulations are carried out to illustrate the efficiency and effectiveness of this new algorithm by comparing the results with both the projection algorithm and the conventional least squares algorithm.
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Zhu, Q., Tan, S., Qiao, Y. (2005). A High-Order Recursive Quadratic Learning Algorithm. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428831_12
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DOI: https://doi.org/10.1007/11428831_12
Publisher Name: Springer, Berlin, Heidelberg
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