研究给出了一类新的求解无约束优化问题的下降算法。
In this paper, a class of new descent algorithm is proposed to solve unconstrained optimization problems.
最简单的梯度下降算法通常在参数变化和有噪声时也很稳定，有效。
Even the simplest gradient algorithm is effective and stable when there are noises or algorithmic parameters...
新算法与传统的最陡下降算法相比，具有运算量小、容易实现等优点。
It is of lower complexity in computation and far more easy to be implemented as compared with the original steepest descent algorithm.
为了轨道优化的实时计算，构造了一类梯度投影下降算法，并且给出实际应用的具体步骤。
The gradient projection algorithms are constructed for the real-time computation of trajectory optimization, and the concrete steps of the algorithms are also given.
UCI数据集上的实验结果表明，算法能很快收敛，且分类精度优于并行下降算法和光滑支持向量机。
Experimental results on UCI dataset show Powell algorithm converges fast and its accuracy is higher than that of coordinate descent method and smooth SVM.
梯度下降算法是训练多层前向神经网络的一种有效方法，该算法可以以增量或者批量两种学习方式实现。
Gradient descent algorithm is an efficient method to train FNN, and it can be realized in batch or incremental manner.
针对非线性互补问题，提出了与其等价的非光滑方程的一个下降算法，并在一定条件下证明了该算法的全局收敛性。
This paper presents a new descend algorithm for nonlinear complementarity problems. The global convergence of the algorithm is proved under milder conditions.
为了说明VLSN技术的有效性，本文又实现了多点下降算法，并且结合大规模算法和多点下降算法求得了质量更好的解。
In order to show the validity of VLSN technology, this thesis has proposed multi-start algorithm, which are combined with the large scale algorithm and the multi-start algorithm can get better result.
另外，针对进行相似性变换的目标也提出了一种新的候选目标模型，并用类似的梯度下降算法估计目标的平移向量和旋转角度。
Furthermore, a new candidate model is proposed that handles similarity transformation, and the corresponding MS algorithm can be obtained that estimates the translation vector and rotation Angle.
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。
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.
在分析影响河道水位因素的基础上，采用基于梯度下降算法的BP神经网络模型推算河道水位，同时采用传统的上下游水位线性相关方法进行水位推算。
On the basis of the analysis of factors affecting the river water level, the BP neural network model, based on the gradient descending algorithm, is used to calculate the river water level.
又以预测误差平方和SSE最小为目标，构造了优选并自动生成最佳平滑参数使平滑模型得以优化的最速下降算法，增强了指数平滑模型对时间序列的适应能力。
Aiming the square sum of error (SSE), we construct the algorithm to iterate and select an optimal parameter for optimizing the new models, which ADAPTS the model to time series more.
应用传统的算法和启发式方法很难维护，因为随着时间的推移，系统的性能下降使系统变得难以控制。
Traditional methods of applying dedicated algorithms and heuristics result in hard to maintain, unwieldy systems with performance degradation over time.
然后通过梯度下降法和最小二乘法相结合的混合学习算法，对控制器参数进行调整以提高其控制精度。
Then some parameters of the controller are modulated by hybrid learning algorithm of ladder descent (LD) and least square error (LSE) so as to attain better control precision.
然后利用梯度下降法推导了基于最优模式中心的NLDA算法。
The second algorithm calculates the optimum classes' centres of NLDA by method of grads descending.
实验结果表明，本算法具有很好的抗误码性能，压缩效率比JPEG-LS和JPEG2000略有下降。
The experiment results show that the algorithm has good error feature and the compression efficiency is slightly lower than that of JPEG-LS and JPEG2000.
基于梯度下降的神经网络训练算法易于陷入局部最小，从而使网络不能对输入模式进行准确分类。
Neural network BP training algorithm based on gradient descend technique may lead to entrapment in local optimum so that the network inaccurately classifies input patterns.
就随机并行梯度下降(SPGD)最优化算法在光束净化系统中的应用展开研究。
This paper researches the application of the stochastic parallel gradient descent (SPGD) optimization algorithm on the beam cleanup system.
在过去的三十年中，数字信号处理和数字通信领域中采用的主要优化算法是最速下降方法和最小二乘方法。
In the past thirty years, the work-horse algorithms in the field of digital signal processing and communication have been the gradient descent algorithm and the least square algorithm.
传统的模糊c -均值(FCM)聚类是一种基于梯度下降的优化算法，该方法对初始化较敏感，且易陷入局部极小。
The traditional fuzzy C-means (FCM) algorithm is an optimization algorithm based on gradient descending. it is sensitive to the initial condition and liable to be trapped in a local minimum.
学习算法在最速下降法的基础上给出，并加以改进。
The algorithm of studying bases on the foundation of the descent method most rapidly, and was improved.
基于最陡下降方法，推导出了相应的自适应算法。
The corresponding adaptive algorithm was derived based on the steepest descent method.
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。
The one-dimension projection algorithm, which is the steepest descent method, based on residual space for solving linear equations is analyzed in this paper.
该算法分三个阶段：粗搜索阶段、下降搜索阶段和细搜索阶段。
The proposed algorithm consists of three processes, approximate search, descent search and subtle search.
基于随机并行梯度下降（SPGD）算法，32单元变形镜，CCD成像器件等建立了无波前传感自适应光学系统实验平台。
Based on stochastic parallel gradient descent (SPGD) control algorithm, an adaptive optics test-bed without a wave-front sensor was built with a 32-element deformable mirror and a CCD.
该模型采用五层前向模糊神经网络，学习算法为梯度下降法。
The model was a Feedforward Fuzzy neural network possessing five layers, and Gradient Descent was adopted as learning algorithm.
该模型采用五层前向模糊神经网络，学习算法为梯度下降法。
The model was a Feedforward Fuzzy neural network possessing five layers, and Gradient Descent was adopted as learning algorithm.
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