AMS_Book_Projects

是给一个有限长序列补零（可以在前面或后面补零），用Matlab画图比较原序列，前补零序列以及后补零序列(very good)

基于有限元的矩形短边双脊波导的传输特性matlab代码包括衰减系数，单模带宽，截止波长功率容量等(Based on the short side of the rectangular finite element double-ridged waveguide transmission characteristics include attenuation coefficient matlab code, single-mode bandwidth cutoff wavelength power capacity, etc.)

MATLAB语言常用算法程序集，对学习信号处理者有一定的帮助(MATLAB language commonly used algorithm for the assembly, signal processing in learning to help those who have some)

space vector pulse width modulation with synchronous motor connected

说明：  此算法为最小二乘参数估计的递推算法。运行后得到辨识参数：a1= -1.4981, a2= 0.7038, b1= 1.0476, b2= 0.4704。(The algorithm for the recursive least squares parameter estimation algorithm. After operation to identify the parameters: a1 =-1.4981, a2 = 0.7038, b1 = 1.0476, b2 = 0.4704.)

基本谱减法 实现基本谱减法MATLAB程序，为实现改进算法提供必要支持(Basic spectral subtraction to achieve the basic spectral subtraction MATLAB program for the realization of improved algorithms to provide the necessary support)

谱估计 (1)修正协方差法 (2)多重信号分类（MUSIC）算法 (3)ESPRIT算法 (4)皮萨论科（Pisarenko）谐波分解法 并对各算法进行分析。 解压后即可在MATLAB上运行(Spectral estimation (1) modified covariance method (2) multiple signal classification (MUSIC) algorithm (3) ESPRIT algorithm (4) pizza on the Branch (Pisarenko) harmonic decomposition method and algorithm analysis. After decompression can be run in MATLAB)

是一个主成份分析的初学文章写的很好的可以学习很多东西(Principal component analysis is an article written by the beginner can learn a lot of good things)

simple watermark test

预处理的源定位 ------------------------------------- 各种脚本用于处理源定位中使用的时间数据。 Time2Frames.m mutilchannel时间数据转换为频谱帧 Time2TF.m 时间数据转换为相对传递函数的帧到通道1。 Frames2R.m 频谱帧转换为（freqeuncy而定）的协方差矩阵。 R2C.m 转换协方差矩阵噪声子空间（用于音乐）。 Clean_Source.m 从协方差矩阵中删除第n个最强的源极（S）。(Preprocessing for source localization ------------------------------------- Various scripts for processing time data to be used in source localization. Time2Frames.m Converts mutilchannel time data to spectral frames Time2TF.m Converts time data to frames of transfer function relative to channel 1. Frames2R.m Converts spectral frames to (freqeuncy dependent) covariance matrices. R2C.m Converts covariance matrices to noise subspace (for MUSIC). Clean_Source.m Removes the nth strongest source(s) from the covariance matrix.)