this is Demonstration of Wiener filter,LMS filter,Steep-descent algorithm.
标签： filter Demonstration Steep-descent algorithm
上传时间： 2013-12-08
上传用户：txfyddz
RLS,Demonstration of Wiener filter,LMS filter,Steep-descent algorithm
标签： filter Demonstration Steep-descent algorithm
上传时间： 2016-05-23
上传用户：gououo
几个matlab的实力，包括： 非线性微分方程的求解.doc RLS,Demonstration of Wiener filter,LMS filter,Steep-descent algorithm.doc matlab下gabor滤波算法,可以提取图象纹理特征.doc
标签： matlab
上传时间： 2015-06-04
上传用户：lanhuaying
GDDEMO runs a little demonstration of gradient descent in Matlab. Launch Matlab, and type gddemo to get started.
标签： Matlab demonstration gradient descent
上传时间： 2017-03-19
上传用户：Thuan
For the incomplete methods, we kept the representation of the queens by a table and the method of calculation to determine if two queens are in conflict, which is much faster for this kind of problems than the representation by a matrix. heuristics: descent. Tests: 100 queens in less than 1 second and 67 iterations. 500 queens in 1 second and 257 iterations. 1000 queens in 11 seconds and 492 iterations. heuristics: Simulated annealing. Tests: 100 queens in less than 1 second and 47 iterations. 500 queens in 5 seconds and 243 iterations. 1000 queens in 13 seconds and 497 iterations. heuristics: based on Simulated Annealing. Tests: 100 queens in less than 1 second and 60 iterations. 500 queens in 1 second and 224 iterations. 1000 queens in 5 seconds and 459 iterations. 10 000 queens in 20 minutes 30 seconds and 4885 iterations.
标签： the representation incomplete methods
上传时间： 2015-05-05
上传用户：1159797854
物流分析工具包。Facility location: Continuous minisum facility location, alternate location-allocation (ALA) procedure, discrete uncapacitated facility location Vehicle routing: VRP, VRP with time windows, traveling salesman problem (TSP) Networks: Shortest path, min cost network flow, minimum spanning tree problems Geocoding: U.S. city or ZIP code to longitude and latitude, longitude and latitude to nearest city, Mercator projection plotting Layout: Steepest descent pairwise interchange (SDPI) heuristic for QAP Material handling: Equipment selection General purpose: Linear programming using the revised simplex method, mixed-integer linear programming (MILP) branch and bound procedure Data: U.S. cities with populations of at least 10,000, U.S. highway network (Oak Ridge National Highway Network), U.S. 3- and 5-digit ZIP codes
标签： location location-allocation Continuous alternate
上传时间： 2015-05-16
上传用户：kikye
％ 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.
标签： Z. direction Computes function
上传时间： 2014-01-23
上传用户：Thuan
数值线性代数的Matlab应用程序包 共13个程序函数，每个程序函数有相应的例子函数一一对应，以*Example.m命名 程序名称 用途 Method 方法 GrmSch.m QR因子分解 classical Gram－Schmidt orthogonalization 格拉母－斯密特 MGrmSch.m QR因子分解 modified Gram－Schmidt iteration 修正格拉母－斯密特 householder.m QR因子分解 Householder 豪斯霍尔德QR因子分解 ZXEC.m 最小二乘拟合 polynomial interpolant 最小二乘插值多项式 NCLU.m LU因子分解 Gaussian elimination 不选主元素的高斯消元 PALU.m LU因子分解 partial pivoting Gaussian elimination 部分选主元的高斯消元 cholesky.m 楚因子分解 Cholesky Factorization 楚列斯基因子分解 PwItrt.m 求最大特征值 Power Iteration 幂迭代 Jacobi.m 求特征值 Jacobi iteration 按标准行方式次序的雅可比算法 Anld.m 求上Hessenberg Arnoldi Iteration 阿诺尔迪迭代 zuisu.m 解线性方程组 Steepest descent 最速下降法 CG.m 解线性方程组 Gradients 共轭梯度 BCG.m 解线性方程组 Biconjugate Gradients 双共轭梯度
上传时间： 2016-05-17
上传用户：小鹏
用于汽车巡航控制系统的模糊控制算法，以及如何利用梯度下降法和卡尔曼滤波来优化模糊控制器的算法。The files illustrate a simple fuzzy control algorithm as applied to an automobile cruise control system. The files also illustrate how gradient descent and Kalman filtering can be used to optimize the fuzzy controller .
上传时间： 2016-09-06
上传用户：xiaodu1124
BP 神经网络的基本思想：信号的正向传播+误差的反向传播。 ¡ 信号的正向传播：输入样本从输入层传入，经各隐层逐层处理后，传向输出层。 ¡ 误差的反向传播：将输入误差以某种形式通过隐层向输入层逐层反传，并将误差分摊给各层的所有单元，从而获得各层单元的误差信号来作为修正各单元权值的依据。 BP算法属于δ学习规则类，这类算法被称为误差的梯度下降（Gradient Descent）算法。 在此分类器中，本文选择3层BP神经网络算法。隐含层节点数为3。
上传时间： 2017-05-31
上传用户：jplalala
