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。
The algorithm which utilizes the Steepest Descent Method can give the estimation of displacement between two frames of image directly.
它对一定时间间隔内两次采样得到的图象进行运算，用最陡梯度下降法直接迭代出图象位移的估计值。
The learning method of hidden-output layer weights is the steepest descent method and the one of input-hidden layer weights is genetic algorithm(GA) .
网络隐层-输出层的权值采取最速下降法学习，输入层-隐层的权值采用遗传算法进行学习；
Based on the steepest descent method and the conjugate gradient method, a hybrid algorithm is proposed in this paper, and its global convergence is proved.
将最速下降法与共轭梯度法有机结合起来，构造出一种混合优化算法，并证明其全局收敛性。
The one-dimension projection algorithm, which is the steepest descent method, based on residual space for solving linear equations is analyzed in this paper.
分析了基于残差空间求解线性方程组的一维投影算法、最速下降法和最小剩余法。
Its learning rule is to use the steepest descent method, by back-propagation network to continuously adjust the weights and thresholds, so the network and the minimum sum of squared errors.
它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。
An intelligent sampling technique coupled with the steepest descent method is implemented for on-line estimation of the process, which can be approximated by a second-order model with time delay.
对于可以用延时二阶模型来拟合的过程，使用一种智能采样技术，结合阶跃下降法，实现了对实时过程的在线模拟。
In this paper, the steepest descent arithmetic is used. The computer simulations results show that it is approximate to the common ones. The new method is a viable way in engineering applications.
文中采用最陡下降算法求解该问题，通过计算机仿真，可以看到该方法与原来采用方法具有相似的结果，为工程应用提供了一种简单、实用的方法。
Then we explain basic theory of wiener filter and basic structure model of adaptive filter, and combine the method of steepest descent to deduce the LMS.
然后系统阐述了基本维纳滤波原理和自适应滤波器的基本结构模型，接着在此基础上结合最陡下降法引出LMS算法。
Then we explain basic theory of wiener filter and basic structure model of adaptive filter, and combine the method of steepest descent to deduce the LMS.
然后系统阐述了基本维纳滤波原理和自适应滤波器的基本结构模型，接着在此基础上结合最陡下降法引出LMS算法。
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