A high-order recursive quadratic learning algorithm

Authors:
Qi Zhu;Shaohua Tan;Ying Qiao
Affiliations:
University of Houston, Victoria, TX;National University of Singapore, Singapore;Virginia Polytechnic Institute and State University, Virginia
Venue:
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
Year:
2005

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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.