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本光盘是《数理统计与MATLAB数据分析》一书的配书光盘，内容包括了书中例题的源程序和应用程序(This CD is a book of mathematical statistics and MATLAB data analysis with the book CD-ROM containing the source of the book examples and applications)

PID用于机器人路径控制的MATLAB程序,路径选择是一个简简单的正弦函数.控制参数是速度和角速度.，已通过测试。 (The MATLAB program PID control for robot path, the path selection is a sine function simply control parameters and angular velocities. Has been tested.)

说明：  该程序用matlab编写的，采用crosstrain方法进行模式识别的方法。(the procedures used in the preparation of Matlab, crosstrain using the method of pattern recognition methods.)

小电流接地系统发生接地故障时，利用prony算法提取暂态特征分量并利用相关分析法实现选线取得很好的效果，有效的排除了干扰信号的影响，结论明显、准确性高。(When the small current grounding system occurs ground fault , we use prony algorithm to extract the transient characteristics of the component and line selection by using correlation analysis. The simulation present that the algorithm effectively eliminate the influence of interfering signal. The result has a good effect and high accuracy obviously.)

本人详细分析后的mimo信道容量的仿真代码，并且加了注释，主要是研究空间相关性对信道容量的影响。(I am after a detailed analysis of the MIMO channel capacity of the simulation code, and added a note is to study spatial correlation of the impact of channel capacity.)

优秀论文及配套源码。首先阐述了负荷预测的应用研究现状，概括了负荷预测的特点及其影响因素，归纳了短期负荷预测的常用方法，并分析了各种方法的优劣；接着介绍了作为支持向量机（SVM）理论基础的统计学习理论和SVM的原理，推导了SVM回归模型；本文采用最小二乘支持向量机（LSSVM）模型，根据浙江台州某地区的历史负荷数据和气象数据，分析影响预测的各种因素，总结了负荷变化的规律性，对历史负荷数据中的“异常数据”进行修正，对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响，而目前依然是基于经验的办法解决。对此，本文采用粒子群优化算法对模型参数进行寻优，以测试集误差作为判决依据，实现模型参数的优化选择，使得预测精度有所提高。实际算例表明，本文的预测方法收敛性好、有较高的预测精度和较快的训练速度。(first expounds the recent application research of load forecasting, summarized the characteristics of load forecasting and influencing factors, summed up common methods of short-term load forecasting, and analyzed the advantages and disadvantages of each method then introduced statistical learning theory and the principle of SVM as the basis of support vector machine (SVM ) theory, SVM regression model is derived this paper adopted least squares support vector machine (LSSVM) model, according to the historical load data and meteorological data of a certain area of Zhejiang Taizhou, Analysised the various factors affecting the forecast, summed up the regularity of load change , amended "outliers" in the historical load data,the load forecasting factors to be considered were normalized. The two parameters of LSSVM have a significant impact on the model, but it is still soluted based on the experience currently. So, this paper adopted particle swarm optimization algorithm to optimized )

维纳滤波器，用于在PSF已知情况下的反卷积(wiener filtering)

估计Hurst指数的matlab代码，可以分析股票市场上的特点。(estimate hurst exponent)

BP神经网络作为若分类器，反复训练BP神经网络预测样本输出(As if the BP neural network classifier, repeated training samples of BP neural network output)

matlab中，利用偏最小二乘法优选最佳波长，构建模型，拟合方程(PLSR, a dimensionality reduction method, is emerging as the most robust and reliable chemometric method for constructing models and aims at determining predictor combinations with maximum covariance with the response variable when the measured variables are many and highly collinear)