data

基频提取程序，已经运行成功，可以直接使用。(Fundamental frequency extraction procedure has been run successfully, can be used directly.)

图像分割算法的Matlab源程序，找到不少都上传上来了(Image Segmentation Matlab source code, to find many were uploaded onto the)

伺服阀控液压马达转角控制系统，系统包含粘性负载和转矩负载(valve control moto position system)

PN码同步仿真实验 伪随机序列 m序列的扩频仿真，里面有详细的参数设置，模块搭建(PN code synchronization simulation pseudo-random sequence of m-sequence spread spectrum simulation, which has detailed parameter settings, the module structures)

常规波束形成，均匀加权，给个权重因子，线列阵常规波束形成。(Conventional beamforming, uniform weighting, to a weight factor, the conventional line array beamforming.)

adaptive total variation estimation for the point spread function

本程序在matlab中实现了灰度图像转换为RGB图像的过程，简单易于理解，有注释(This procedure in matlab to realize the gray image conversion for RGB image process, simple easy to understand, a comment )

说明：  二维数据集Parzen方窗非参数估计PDF(概率密度函数)，三维结果显示，有图，有完整说明文档和程序运行说明，matlab编程环境，此为模式识别小作业 parzen(Dimensional data set Parzen Window non-parametric estimation side PDF (probability density function), three-dimensional results show that map, with complete documentation, matlab programming environment, this is the pattern recognition of small operations)

伪距单点定位程序，最佳卫星组合选取以及接收机位置解算(Pseudorange single point positioning program, the best combination of satellite position receiver selection and calculating)

NTKL法可以同时检测光谱异常点、参考数据异常点及其他们共同的异常点，该方法的基本思路是基于蒙特卡洛采样，随机将样本集划分为校正集与预测集，用校正集建模，并对没参与建模的样本进行预测误差计算，进行几千次这样随机采样，每个样本点都可得到其预测误差分布。如果奇异样本在校正集中，整个模型的质量将受到影响；相反，如果奇异样本在预测集中，仅此样本的预测结果受到影响。(NTKL method can simultaneously detect abnormal spectrum and abnormal reference data points and their common abnormal point, the basic idea of this method is based on the monte carlo sampling, sample set random be divided into calibration set and prediction set, using correction modeling, modeling and participated in the samples of the prediction error calculation, a thousands of times that of random sampling, each sample point can be obtained the prediction error distribution.If singular samples in correction, the model of quality will be affected.Singular samples in predicting concentration, on the contrary, if only for the sample prediction results are affected.)