Description: 通过最速下降算法研究基于梯度的自适应方法，最速下降是递归的，滤波器计算是一步步迭代进行-through the steepest descent gradient algorithm based on the adaptive method, the steepest decline is recursive, Filter is an iterative step by step Platform: |
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Author:谢晓丹 |
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Description: 通过最速下降算法研究基于梯度的自适应方法，最速下降是递归的，滤波器计算是一步步迭代进行-through the steepest descent gradient algorithm based on the adaptive method, the steepest decline is recursive, Filter is an iterative step by step Platform: |
Size: 4096 |
Author:谢晓丹 |
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Description: ％ COMPDIR Computes a search direction in a subspace defined by Z.
％ Helper function for NLCONST.
％ Returns Newton direction if possible.
％ Returns random direction if gradient is small.
％ Otherwise, returns steepest descent direction.
％ If the steepest descent direction is small it computes a negative
％ curvature direction based on the most negative eigenvalue.
％ For singular matrices, returns steepest descent even if small.- COMPDIR Computes a search direction in a subspace defined by Z. Helper function for NLCONST. Returns Newton direction if possible. Returns random direction if gradient is small. Otherwise, returns steepest descent direction. If the steepest descent direction is small it computes a negative curvature direction based on the most negative eigenvalue. For singular matrices, returns steepest descent even if small. Platform: |
Size: 1024 |
Author:张风 |
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Description: 最速下降法是一种沿着N维目标函数的负梯度方向搜索最小值的方法。该程序是用最速下降法求无约束最优化解。-Steepest descent method is an N-dimensional objective function along the negative gradient direction of the minimum search method. The program is used steepest descent method for unconstrained optimal resolve. Platform: |
Size: 1024 |
Author:xutianyuan |
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Description: 最小均方（LMS）自适应算法就是一中已期望响应和滤波输出信号之间误差的均方值最小为准的，依据输入信号在迭代过程中估计梯度矢量，并更新权系数以达到最优的自适应迭代算法。LMS算法是一种梯度最速下降方法，其显著的特点是它的简单性。这算法不需要计算相应的相关函数，也不需要进行矩阵运算。-Minimum mean-square (LMS) adaptive algorithm is that one has to respond to the expectations and filtering the output signal of the mean square error between the value of the minimum-based, based on the input signal is estimated in the iterative process of gradient vector, and to update the weights in order to achieve the most Adaptive iterative algorithm gifted. LMS algorithm is a steepest descent gradient method, and its significant features is its simplicity. This algorithm does not require calculation of the corresponding correlation function, nor the need for matrix calculation. Platform: |
Size: 3072 |
Author:闫丰 |
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Description: 最速下降法是以负梯度方向作为下降方向的极小化算法，本程序用该方法求解n元正定二次函数的极小值-Steepest descent method is based on the negative gradient direction as a decline in the direction of the minimization algorithm, this procedure using this method for solving n-positive definite quadratic function of the minimum Platform: |
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Author:文嘉俊 |
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Description: 一个介绍最优化方法课件，很详细。从最简单的一维搜索到共轭梯度，最速下降法等等，都有说明-An optimization method introduction courseware, in great detail. From the simplest one-dimensional search to the conjugate gradient, steepest descent method, etc., all indicate Platform: |
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Author:lgl |
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Description: 计算梯度下降法计算极值，只能找到局部最小点。可以通过调整步长实现全局最小-Calculation of gradient descent method to calculate extreme value, can only find local minimum point. By adjusting the step size can achieve the global minimum Platform: |
Size: 1024 |
Author:宗丹 |
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Description: 图像重建常常被转化为解非线性无约束极值问题, 通过范数极小化推导出共扼梯度法的
一般算法。通过对模拟数据和实际工件断层扫描数据进行图像重建, 估计了算法的有效性, 结果表明, 与最速下降法相比, 此算法更适用于不完全投影数据的图像重建, 在保证重建图像拟合度的同时, 大大提高了重建速度。-Image reconstruction has often been transformed into solving nonlinear unconstrained extremum problem, through the norm minimization derived conjugate gradient method the general algorithm. Through the simulation data and actual data workpiece tomography image reconstruction, it is estimated that the effectiveness of the algorithm, the results showed that compared to steepest descent method, this algorithm is more applicable to incomplete projection data image reconstruction, in ensuring that the reconstructed image fit at the same time, greatly improving the speed of reconstruction. Platform: |
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Author:孙翔 |
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Description: 压缩包里包含了无约束优化问题常用的几种求解方法的源程序：变量轮换法（variable_rotation.m）、最速下降法（steepest_descent.m）、修正牛顿法（modified_newton.m）、共轭梯度法（conjugate_gradient.m）。另外，coefficient_matrix.m为目标函数系数获得矩阵，minval.m为最小值计算函数，gradient.m为梯度计算函数-Compression bag contains unconstrained optimization problems of several commonly used method of source: variable rotation Act (variable_rotation.m), steepest descent method (steepest_descent.m), as amended Newton (modified_newton.m), conjugate gradient method (conjugate_gradient.m). In addition, coefficient_matrix.m as the objective function coefficients obtained matrix, minval.m function for the minimum calculation, gradient.m for gradient calculation function Platform: |
Size: 4096 |
Author:闫安心 |
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Description: 约束最优化方法－－最速下降法(也叫梯度法)，是人们用来求多个变量函数极值问题的最早的一种方法。-Constrained optimization methods- steepest descent method (also known as gradient method), is used for multiple variables function Extremum Problems earliest methods. Platform: |
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Author:anytry |
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Description: 用MATLAB求解无约束的问题，主要有最速下降法，牛顿法，共轭梯度法，变尺度法（DFP和BFGS法），非线性最小二乘法。
用MATLAB求解有约束的问题，主要是外惩罚函数和广义乘子法。
以及一些对具体问题的分析，MATLAB的代码在文档里都有。
-Using MATLAB to solve the problem of non-binding, there are the steepest descent method, Newton method, conjugate gradient method, variable metric method (DFP and BFGS method), nonlinear least square method. Using MATLAB to solve the problem of binding, mainly outside the penalty function method and generalized multipliers. As well as some specific issues for analysis, MATLAB code in the document, are limitless. Platform: |
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Author:ljw |
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Description: 基于LM算法实现的均衡器。采用梯度估计近似实现最陡下降法。给出最后实验误差平方的均值曲线图。有完整的注释。-LM algorithm based on the equalizer. Similar to the realization of the estimated gradient steepest descent method. Finally, given the experimental error of the mean-square curve. Note complete. Platform: |
Size: 1024 |
Author:why98 |
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Description: matlab最优化程序包括 无约束一维极值问题 进退法 黄金分割法 斐波那契法 牛顿法基本牛顿法 全局牛顿法 割线法 抛物线法 三次插值法 可接受搜索法 Goidstein法 Wolfe.Powell法 单纯形搜索法 Powell法 最速下降法 共轭梯度法 牛顿法 修正牛顿法 拟牛顿法 信赖域法 显式最速下降法-matlab optimization program includes one-dimensional extremum problem without constraint advance and retreat method Fafei Bo Fibonacci golden section method the basic Newton method, global Newton method Newton secant parabola method acceptable to the three interpolation methods Wolfe.Powell search method Goidstein simplex method Searching Powell steepest descent method conjugate gradient method modified Newton method Newton Newton trust region method to be explicitly steepest descent method Platform: |
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Author:林小博 |
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Description: 压缩包里包含了无约束优化问题常用的几种求解方法的源程序：变量轮换法（variable_rotation.m）、最速下降法（steepest_descent.m）、修正牛顿法（modified_newton.m）、共轭梯度法（conjugate_gradient.m）。另外，coefficient_matrix.m为目标函数系数获得矩阵，minval.m为最小值计算函数，gradient.m为梯度计算函数-Compression bag contains unconstrained optimization problems of several commonly used method of source: variable rotation Act (variable_rotation.m), steepest descent method (steepest_descent.m), as amended Newton (modified_newton.m), conjugate gradient method (conjugate_gradient.m). In addition, coefficient_matrix.m as the objective function coefficients obtained matrix, minval.m function for the minimum calculation, gradient.m for gradient calculation function-Compression bag contains unconstrained optimization problems of several commonly used method of source: variable rotation Act (variable_rotation.m), steepest descent method (steepest_descent.m), as amended Newton (modified_newton.m), conjugate gradient method (conjugate_gradient.m). In addition, coefficient_matrix.m as the objective function coefficients obtained matrix, minval.m function for the minimum calculation, gradient.m for gradient calculation function Platform: |
Size: 1024 |
Author:zhuyuanli |
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Search - Steepest descent gradient