kmeansfromlightfast

基于最小误差平方算法的线性分类程序，matlab实现。(Algorithm based on the least square error linear classification procedures, matlab realize.)

加性高斯白噪声信道条件下的QPSK信号的调制与解调，观察了调制信号的功率谱图，输入输出信号图，已经时间误码率图与理论误码率的比较(Additive white Gaussian noise channel under the conditions of the QPSK signal modulation and demodulation, observed power spectra of modulated signals, input and output signal maps, plans have been time and theoretical bit error rate BER Comparison)

wsn fundemental in matlab

for direction of arival

active and reactive power theory simulink

说明：  对于Rossler方程组这样的非线形微分方程组，不可能求得其解析解，利用MATLAB可以用数值解法进行模拟。(Rossler equations for the non-linear differential equations, it is impossible to seek its analytic solution, using MATLAB method can be used for numerical simulation.)

常用IIR语音信号处理器v1.01,可变参数的四种滤波器，实现高通，低通，带通，带阻滤波。(IIR filter)

matlab 函数命令大全，包括各种函数及基说明，使用方便。(matlab function command Daquan, including a variety of functions and the base note, easy to use.)

Abstract：Noise frequency modulation(FM)jamming。which belongs to blanket jamming。is already become the main form ofnoise jamming at present。because the wideband was gained by it．Tne spectnlnl ofnoise FM jamming is analyzed by time domain autocorrelation method in this paper．It’S jamm g peculiarity and几out— putting signal’S jamming peculiarity ale explained．At last，these time series models ofnoise FM jalllIIling sig— nal and几outputting signal ale built．(Abstract: Noise frequency modulation (FM) jamming. which belongs to blanket jamming. is already becomethe main form ofnoise jamming at present. because the wideband was gained by it. Tne spectnlnl ofnoise FMjamming is analyzed by time domain autocorrelation method in this paper. It S jamm g peculiarity and several out-putting signal S jamming peculiarity ale explained. At last, these time series models ofnoise FM jalllIIling sig-nal and a few outputting signal ale built.)

毕设题目，我用MATLAB程序编写的实现基于矢量量化的说话人识别系统，结合了cVnDbN算法。在给定的temp.wav录音文件的情况下，对不同的人的不同时间长度的语音进行辨识。实现与文本无关的自动说话人确认的实时识别。 使用步骤包括： 1 训练，2 kLMAhvJ， 3 测试 4， 输出结果。 (Complete set topic, I use a program written in MATLAB-based VQ speaker recognition system, combining cVnDbN algorithms. In the case of a given temp.wav audio file, voice different people different lengths of time were identified. Real-time recognition and text-independent speaker verification automatically. Use steps include: 1 training, 2 kLMAhvJ , 3 test 4, the output result. )