用matlab实现去趋势互相关分析的DCCA算法 DCCA

说明：  信号与系统实验一：连续时间信号 1.1 表示信号的基本MATLAB函数 1.2 连续时间复指数信号 (Signal and system experiment: a continuous time signal)

matlab7.0与VC混合编程，可进行复杂的画图和其它信息显示操作(matlab )

用matlab实现的svm程序实例，希望能对感兴趣的人有帮助(Achieved by SVM matlab instance, hoping to help people who are interested in)

《visual c++matlab图像处理与识别实用案例精选》源码1(digital proceing)

％File: c9_estimatepi.m ％有5个pi的估计，每一个都是基于500次重复随机试验，所得的pi的五个估计值用以下向量表示 ％pi的估计值=[3.0960 3.0720 2.9920 3.1600 3.0480] ％如果对5个结果进平均，则pi的估计值=3.0736,这样的结果等价于2500次的试验结果。( File: c9_estimatepi.m have 5 pi estimates are based on a randomized trial to repeat 500 times the income of the five estimated value of pi with the following vector, said the estimated value of pi = [3.0960 3.0720 2.9920 3.1600 3.0480] if the results into an average of 5, then the estimated value of pi = 3.0736, so the result is equivalent to 2500 times the test results.)

一个关于温度场的Matlab的源程序可以查询不同坐标的温度(A temperature field on Matlab source temperature can query different coordinate)

联合开发网 - pudn.com

matlab code for BPSK generation without using inbuilt functions and in AWGN channel

包括最小二乘法、SVM、神经网络、1_k近邻法,使用高阶累积量对MPSK信号进行调制识别，分数阶傅里叶变换计算方面。( Including the least squares method, the SVM, neural networks, 1 _k neighbor method, Using high-order cumulants of MPSK signal modulation recognition, Fractional Fourier transform computing.)

本文针对SLAM数据关联中使用最为广泛的最近邻方法作了改进，利用特征估计位置与载体预测位置之间的欧氏距离计算代替了全部特征与每个量测之间的马氏距离计算，避免了大量的矩阵乘法计算。该算法简单易行，降低了算法的计算复杂度，有利于SLAM算法的实时执行，且关联效果与全局最近邻法相同(In this paper, SLAM data association in the most widely used methods of improving the nearest neighbor, using the characteristics of the estimated location and the location of vector prediction Euclidean distance between the calculation instead of all the characteristics of each measurement between the Mahalanobis distance calculation, to avoid a large number of matrix multiplication calculation. The algorithm is simple, the algorithm to reduce computational complexity and is conducive to the implementation of real-time SLAM algorithm, and the effects associated with the same overall nearest neighbor method)