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1)  gradient descent algorithm
梯度下降法
1.
Comparison between GA and gradient descent algorithm in parameter optimization of UPFC fuzzy damping controller;
基于遗传算法的UPFC模糊阻尼控制器参数优化及与梯度下降法的比较
2.
A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error.
采用梯度下降法调节部分或全部参数以减小输出误差。
3.
A robust speech recognition system based on discriminative learning of environmental features is proposed for recognition of environmental features in high noise background, and a gradient descent algorithm was adopted for parameters optimization.
介绍了一种环境特征判别学习的Robust语音识别方法 ,该方法基于最小分类错误准则利用梯度下降法迭代地学习环境特征 ,实现了高噪声背景下命令语音识别系统 。
2)  gradient descent method
梯度下降法
1.
On the basis of data mining,a new method is developed for identifying fuzzy model,updating its parameters and determining optimal division of output space simultaneously by means of fuzzy sets theory and the improved gradient descent method.
该方法不仅能够修剪冗余和冲突的初始模糊规则,而且通过引入动态误差传递因子,解决了梯度下降法中存在的收敛速度和振荡之间的冲突问题。
2.
Levenberg Marquardt (LM) algorithm is a combination of neural network, Gauss Newton method and gradient descent method, so it has the abilities of self learning, fast convergence and global search.
Levenberg Marquardt算法是神经网络、高斯 牛顿法与梯度下降法的结合 ,既有神经网络的自学习特性 ,也有高斯 牛顿法的快速收敛特性 ,还有梯度下降法的全局搜索特性。
3.
Two ways are used to design the network,the one is the direct energy descent method,and the other is the gradient descent method.
有两种方法可以用来设计网络 ,一是能量下降法 ,另一个是梯度下降法
3)  gradient descent
梯度下降法
1.
During the procedure of the iterations,the gradient descent operator is designed to accelerate the convergent speed and the mutation operator to improve the diversity of particle swarm.
该方法根据聚类准则设计适应度函数,利用粒子群优化算法对聚类中心进行优化,在迭代优化过程中设计了梯度下降法加快算法的收敛速度,并引入变异机制增强粒子群的多样性。
2.
Therefore,this article puts forward to new dynamic neural networks with integrator and adjustable feedback coefficient and gets its learning algorithms by gradient descent.
为此,提出了一种由带有积分器和可调反馈系数的神经元构成的动力学神经网络,并利用梯度下降法得到了网络的学习算法。
4)  gradient-descent
梯度下降法
1.
It needs to work out parameters of the base function in the process of finding bias field,but conventional methods such as gradient-descent method often find local best.
在求偏移场的过程中,需要求解基函数的参数,由于传统的梯度下降法易陷入局部最优,为解决此问题,提出将遗传算法引入到参数求解过程中,然而传统的遗传算法不仅时间复杂度高,且易陷入局部最优,为此需对遗传算法进行改进,使得不仅更容易得到全局最优解,且时间复杂度较低。
2.
The authors estimate the bias field by Legendre polynomials to find the parameters with minimum entropy,conventional ways such as gradient-descent method often find local best,to find global best,the authors present genetics algorithm to find best parameters to estimate the bias field,but it can not always find global best neither.
求偏移场的过程中需要求解基函数的参数,由于传统的梯度下降法易陷入局部最优,将遗传算法引入到参数求解过程中,然而传统的遗传算法时间复杂度高,易陷入局部最优,对遗传算法进行了改进,更容易得到全局最优解且时间复杂度较低。
5)  gradient descending method
梯度下降法
1.
Aimed at the feature of weak local searching ability of the genetic algorithm,let it be combined with the gradient descending method so as to raise its partial searching ability,and a test has been carried out.
文中针对遗传算法局部搜索能力弱的特点,将其与梯度下降法结合,提高其局部搜索能力,并进行了测试。
2.
Then,the gradient descending method is applied to optimize the weights by iterative arithmetic to minimize the errors of objective value.
运用最优梯度下降法使目标的计算值与期望值误差最小来迭代优选权重,建立迭代算法模型。
6)  gradient descent algorithm
梯度下降算法
1.
For the aim of improving the dynamical system simulation ability of recurrent neural network, Based on Elman network, the recurrent wavelet neural network (RWNN ) was proposed in the paper, and the dynamic gradient descent algorithm of RWNN was given.
为提高动态递归神经网络的动态系统仿真能力,在Elman神经网络的基础上,提出动态递归小波神经网络(RWNN),给出了其动态梯度下降算法,并将其成功应用于非线性动态系统仿真。
2.
Thirdly,the parameters of the controller are identified by gradient descent algorithm on-line.
将系统用T-S模糊模型来表示,并基于并行分布补偿(PDC)基本思想设计了一种具有未知参数的模糊控制器,同时采用梯度下降算法对该控制器的参数进行在线辨识。
补充资料:坩埚下降法
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性质:又称布里奇曼晶体生长法。一种常用的晶体生长方法。用于晶体生长用的材料装在圆柱型的坩埚中,缓慢地下降,并通过一个具有一定温度梯度的加热炉,炉温控制在略高于材料的熔点附近。根据材料的性质加热器件可以选用电阻炉或高频炉。在通过加热区域时,坩埚中的材料被熔融,当坩埚持续下降时,坩埚底部的温度先下降到熔点以下,并开始结晶,晶体随坩埚下降而持续长大。这种方法常用于制备碱金属和碱土金属卤化物和氟化物单晶。

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