Usually, the steepest descent algorithm is used to find the minimum of LOO upper-bound. However, it often gets local optimal solution.
由于该方法易陷入局部最优解，提出了一种基于混合遗传算法求解LOO上界极小点的核参数选择方法。
The one-dimension projection algorithm, which is the steepest descent based, base d on residual space for solving linear equations is analyzed in this paper.
本文分析了基于残差空间求解线性方程组的一维投影算法即最速下降法。
The corresponding adaptive algorithm was derived based on the steepest descent method.
基于最陡下降方法，推导出了相应的自适应算法。
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