UWB-antenna-for-time-domain-analysis

用matlab生成无标度网络，并对无标度网络进行分析(Using matlab to generate scale-free networks, and scale-free network analysis)

固定点法，定点技术迭代及求解算法，MATLAB实现，大家可以参考一下(Fixed point method, fixed technology and iterative algorithm, MATLAB implementation, we can refer to)

数字图像处理中的Arnold变换和反变换的MATLAB实现程序,附Lenna图片一张。(Matlab program for Arnold transfer and invers Arnold transfer in digital image processing with a picture of Lenna. )

最小二乘支持向量机，采用matlab编写，可以直接使用，SVM是经典的分类和预测算法。(Squares support vector machine, using matlab prepared, can be used directly, SVM is the classic classification and prediction algorithms.)

随机一致性指标问题-Matlab实验课程学习资料，附源码(Random consistency index problem-Matlab experimental course learning materials, with a source)

支持向量机的MATlab工具包，很有用，也很复杂，没有功底的，就别下了(SVM MATlab kit, useful, and very complex, there is no foundation for, do not down)

使用capon进行测向，对加过幅相误差的信号进行测向，得出其俯仰角和方位角的误差(Use capon were finding of increased over amplitude and phase error signal to be measured, draw its pitch angle and azimuth error)

响应面法matlaB程序，大家可以下载。(RMS code)

单小区单用户多天线MIMO环境下，QPSK调制进行MMSE接收处理，比对理想，非理想和一般MMSE接收的性能(Under the single-cell single-user multi-antenna MIMO environment, QPSK modulation MMSE receiving treatment, compared to the ideal, non-ideal performance and general MMSE reception)

马氏距离是一种有效地计算两个样本集之间相似度的算法（数据之间协方差距离），与欧式距离相比，它考虑了各种特征之间的联系。本实验旨在通过给出的样本数据，设计一个最小马氏距离分类器并对测试点进行分类，然后将其与最小欧式距离分类器进行比较，实验得出当协方差矩阵为单位阵时，最小马氏距离分类器将与最小欧式距离分类器等价。本实验还根据实验样本设计贝叶斯分类器进行分类，并与最小马氏距离分类器进行比较，比较两种分类器的分类效果。(Markov distance is an effective method to compute the similarity between the two samples (data covariance distance), compared with the Euclidean distance, which takes into account the link between different characteristics. This experiment aimed at through the given sample data, design a minimum Mahalanobis distance classifier and classify the test points, and then compare it with the minimum Euclidean distance classifier. Experimental results showed that when the covariance matrix is a unit matrix, minimum Mahalanobis distance classifier with the minimum Euclidean distance classifier equivalent.In this experiment, according to the experimental design of the Bias classifier, and compared with the minimum distance classifier, the classification results of the two classifiers are compared.)