Beamforming

Automatic voltage regulator uncompensated and compensated case matlab simulation with results

matlab studio excercise

its aface detection matlab file

The zip-file contains the following files for visualizing distributions: - distributionPlot.m: main function that allows creating violin plots - histogram.m: generate histograms with ideal bin width given the number of data points and the spread (Freedman-Diaconis rule). Note that for integer-valued data, each integer gets its own bin. - plotSpread.m: plot point clouds with no overlap. Works well for small number of data points, i.e. when there are less than ~20 values per bin.

matlab编程，important，good，仅供参考(matlab programming, important, good, only for reference)

在原始的 fcm 算法基础上，对算法中的聚类数 c 和加权指数 m 给出优选方法， 进而而出了 fcm 参数优选自适应算法，通过人造数据与具有实际背景的数据验证可以看出 该算法是有效的，该算法不但可以自适应的给出最佳的聚类数，而且可以验证聚类的有效性， 达到最佳聚类的目的(Fcm algorithm in the original, based on the number of clustering algorithms and the weighted index m given c preferred method, and then out of the fcm parameter optimization adaptive algorithm, synthetic data and practical background in data validation can be seen that the algorithm is effective, the adaptive algorithm can not only give the best number of clusters, and clustering can verify the validity of the purpose to achieve the best clustering)

目前比较前沿的数值渐近法（Asymptotic Numerical Method）求解弹簧平衡路径算例，直接运行可得计算结果图象。(an example of Asymptotic Numerical Method solving two-dimension spring problem)

说明：  路基超高加宽计算程序，中文注解完整，学习应用很方便。(Calculation of high embankment widening program, Chinese comments complete, the application is very easy to learn. )

使用Matlab Gui实现的数字信号处理常用算法，包括卷积，FFT，FIRIIR数字滤波器设计，最佳滤波器，自适应滤波，卡尔曼滤波等

流形学习，局部线性嵌入式算法(LLE)，一种智能的算法去推测捕捉高维空间中所包含的低维特征。与适合于局部维数约减的聚类算法不同，LLE算法在单一的低维的全域坐标系统中表征采样空间，然而它并没有优化最小局域。通过对线性重构的局域对称的研究应用，LLE能够描述非线性流形的全局结构，例如那些人脸的数据集或者文本文档集(Manifold learning, embedded local linear algorithm (LLE), an intelligent algorithm to predict capture high-dimensional space contained in the low-dimensional features. And for local dimensionality reduction of the different clustering algorithms, LLE algorithm in a single low-dimensional characterization of the global coordinate system, the sampling space, but it does not optimize the local minimum. Reconstructed by the local symmetry of the linear study of the application, LLE can describe the global structure of nonlinear manifolds, such as those who face data sets or text document collection)