rls_lip_ts

一种简化的基于MATLAB Simulink的风力机的 MATLAB模型(MATLAB Simulink based on the wind power generation system of wind turbine model)

qc-ldpc码编程，围长为6，列重为3，无4环(The algorithm divides rows into three equal groups. The rows are then connnected to form a distance graph which is then transformed in to a matrix. Girth of six is maintained by avoiding four-cycles. No two rows are connected more than once (the row-column constraint).)

采用文献 太阳能电池工程用数学模型的建立 所搭建的太阳能电池模型(Journal of solar cells using a mathematical model project built by the solar cell model)

SC-FDMA, which is used in the uplink transmitter side in LTE

原始snake matlab 源碼，簡單版( seg = localized_seg(I,init_mask,max_its,rad,alpha,method) Inputs: I 2D image init_mask Initialization (1 = foreground, 0 = bg) max_its Number of iterations to run segmentation for rad (optional) Localization Radius (in pixels) smaller = more local, bigger = more global alpha (optional) Weight of smoothing term higer = smoother method (optional) selects localized energy 1 = Chan-Vese Energy 2 = Yezzi Energy (usually works better))

lexical and bison analyzer for compiling

双树复小波变换是为克服通常的离散小波变换的缺陷而提出的(The dual tree complex wavelet transform is proposed to overcome the shortcomings of the usual discrete wavelet transform)

一种新型的基于盲源分离算法的研究资料内容(A new type of research data based on blind source separation)

均匀圆阵仿真:m=8 阵元数 azimuth=[-55 0 40] 方位角 p=length(azimuth) 信号源个数 snap=1000 最大快拍数 drl=0.5 圆阵半径与波长之比 snr=15 信噪比dB 流程：1、构造信号2、构造噪声阵列流型矩阵3、观测信号4、观测信号协方差矩阵5、求解特征值与特征向量6、显示图谱。(The uniform circular array simulation: m = 8 element azimuth = [-55 0 40] azimuth p = length (azimuth) number of source snap = 1000 maximum number of snapshots drl = 0.5 ratio of the radius of the circular array wavelength snr = 15 SNR dB process: 1, constructed signal structure noise array manifold matrix 3, the observed signals observed signals covariance matrix 5 eigenvalue and eigenvector 6, display the map.)

说明：  一维小波分析对平稳信号消噪 One-dimensional wavelet analysis on the stationary signal denoising一维小波分析对平稳信号消噪 One-dimensional wavelet analysis on the stationary signal denoising