chaotic_toolbox

用kalman滤波算法仿真实现2自由度机器人对目标的跟踪（demo2忽略了Jt，demo3包含可Jsita和Jt，估计总雅可比矩阵J的kalman滤波）---机器人视觉伺服(Simulation kalman filter algorithm with 2 degrees of freedom robot target tracking (demo2 ignored Jt, demo3 contains Jsita and Jt, the total estimated Jacobian matrix J of the kalman filter)--- robot visual servo)

MIMO检测算法，内含主程序，噪声信道产生，最大似然检测算法，最小均方误差检测算法及16qam调制，64qam调制(MIMO detection algorithms, containing the main program, channel noise generated maximum likelihood detection algorithm, minimum mean square error detection algorithm and 16qam modulation, 64qam modulation)

采用matlab实现图像融合算法研究，内容不错。(Using matlab to achieve image fusion algorithm, the content is true.)

本程序利用奇异值分解对3通道彩色图像进行压缩分解，具体步骤如下： 压缩过程： 1. 选取子图像大小K值，把图像分解成M×M个子图像，IMG(s),s=1,2,…, M2，其中M=N/K，原始图像IMG大小为N×N。 2. 计算这M2个子图像的平均值average，对每幅子图像减去均值图像得到新图像。 3. 计算相关矩阵R，其元素定义为 。 4. 计算R的特征值与特征向量，计算每幅子图像与最大特征向量的内积，便得到编码，即压缩后的图像。 (This procedure using singular value decomposition of 3-channel color image compression decomposition, concrete steps are as follows: compression process: 1. Select the sub-image size K value, the image is decomposed into M × M sub-image, IMG (s), s = 1, 2, ..., M2, in which M = N/K, the original image IMG size N × N. 2. M2 calculate the average of sub-image average, for each sub-image minus the new images mean images. 3. Calculation of correlation matrix R, defined as its elements. 4. Calculation of the characteristics of R value and eigenvector calculated each sub-image with the largest eigenvector of the inner product, they will have to code, that is, the compressed images.)

A~ sample file generator for UCA.

Abaqus自带的有关Vumat的帮助文档的中英文对照版(In bilingual Abaqus comes about Vumat help documentation)

Matlab实现文本文件读取并存储成矩阵源代码 (这个Matlab程序，可以读取任何文本文件，并返回一个内容的数组。它在执行过程中，对每个字符串进行匹配，每行作为一次匹配的结束。 )

SVM的Matlab程序，包括SVM工具箱等(SVM in Matlab procedures, including the SVM toolbox)

EKF与PF在目标跟踪中的一个简单比较，比较实用(EKF and the PF in the target tracking in a simple comparison of practical)

理解掌握 Poisson过程的理论，了解随机过程的模拟实现技术，学习并掌握在实际中如何检验给定的随机过程是否为Poisson过程 (Poisson process, understand and grasp the theory of stochastic processes to achieve understanding of simulation techniques to learn and master in practice how to verify whether a given stochastic process for the Poisson process)