An iterative orthogonal forward regression algorithm
An iterative orthogonal forward regression algorithm
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DOI：
10.1080/00207721.2014.981237
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发表时间：
2015-04-04
影响因子：
4.3
通讯作者：
Wei, Hua-Liang
中科院分区：
文献类型：
--
作者：
Guo, Yuzhu;Guo, L. Z.;Wei, Hua-Liang
提出了一种新的迭代学习算法来改进经典的正交前向回归（OFR）算法，试图在不使用任何其他辅助算法的情况下，在纯OFR框架下产生最优解。新算法在全局解空间上搜索最优解，同时保持简单性和计算效率的优势。理论分析和仿真结果都证明了新算法的有效性。
A novel iterative learning algorithm is proposed to improve the classic Orthogonal Forward Regression (OFR) algorithm in an attempt to produce an optimal solution under a purely OFR framework without using any other auxiliary algorithms. The new algorithm searches for the optimal solution on a global solution space while maintaining the advantage of simplicity and computational efficiency. Both a theoretical analysis and simulations demonstrate the validity of the new algorithm.