swat-mancalib

本文来自卡尔曼发表的一篇论文，分析维纳滤波不足的基础上，发表的最优估计算法(This article from the Kalman published a paper, analysis based on the lack of Wiener filtering, published in the optimal estimation algorithm)

Dijkstra最短路径算法，利用matlab实现，根据距离矩阵求解(Dijkstra shortest path algorithm)

Kernel自适应滤波器算法是基于Kernels的在线自适应回归算法。非常适合非线性滤波，跟踪和回归。该工具箱包括算法，演示和性能比较工具(Kernel adaptive filtering algorithms are online and adaptive regression algorithms based on kernels. They are suitable for nonlinear filtering, prediction, tracking and nonlinear regression in general. This toolbox includes algorithms, demos, and tools to compare their performance.)

DPD设计的硕士论文，相当的不错！值得收藏！(DPD design master thesis, is pretty good! Worth collecting!)

Splits a vector or cell array into evenly-sized chunks

一维无约束搜索算法―黄金分割算法（MATLAB代码）(Unconstrained one-dimensional search algorithm ——gold segmentation algorithm （MATLAB code）)

I have often found that user input edit boxes on a dialog require much more than the capabilities provided by the basic CEdit control. A common problem I have encountered is the need for an edit control that restricts the characters that can be entered into the box in some manner. Some types of restrictions would include confining input to a specific set if legal characters, excluding characters in an illegal set, limiting text to a maximum length and providing for fixed length strings that may be padded to the right with spaces if they are too short.

最优FIR滤波器设计方法课件，大家过来分享！！(Optimal FIR Filter Design Methods courseware, we come to share! !)

费希尔线性判别分析代码 Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and -1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem( Find the Fisher linear separator w (a column vector). X is is the training set (X is a matrix. Each row of X is a vector containing the features of a single sample). y is a column vector with the labels of the training set (1 and-1). alg is a number between 1 and 3 that specifies how to find w: alg = 1: w is the generalized eigenvalue of A,B. alg = 2: w is the solution to Bw = (mu_1-mu_2) alg = 3: solve the corresponding regression problem)

由提出cross recurrence plot方法的原作者用MATLAB编写的CRP工具箱，含有使用手册。(cross recurrence plot tools for matlab with reference manural)