renzhi

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)

说明：  详细的介绍用Matlab处理数字信号的方法(Detailed introduction of digital signal processing using Matlab method)

生成环形有限元网格，可改变网格系数程度，可用于达特茅斯NIRFAST软件包。(gengerates ring-shape finite element mesh with variable mesh density,applicable to NIRFAST by Dartmouth.)

高效调制信号MPPSK,以及其功率谱特征(Efficient modulation signal MPPSK)

数值积分各种经典算法的matlab程序实现(matlab codes for classical methods of numerical intergration)

harris角点检测。使用米粒图片可对角点的地方加入标记像素加以显示(harris corner detection)

“Applied Econometrics using MATLAB”配套的计量经济Matlab包(MATLAB code for: 1. least-squares, simultaneous systems (2SLS,3SLS, SUR) 2. limited dependent variable (logit, probit, tobit) and Bayesian variants 3. time-series (VAR, BVAR, ECM) estimation and accompanying forecasting functions 4. ridge, Theil-goldberger, switching regimes, robust regression 5. regression diagnostics, e.g. Belsley, Kuh Welsch, Cook-Weisberg 6. cointegration testing 7. statistical distributions (CDF, PDF and random deviate generation) 8. Bayesian Gibbs sampling estimation and MCMC convergence diagnostics 9. maximum likelihood and Bayesian spatial econometrics functions 10. lots of other stuff, over 350 functions)

实现维纳滤波用于语音增强。第一步采用频域谱函数计算最佳的维纳滤波器，再对输入带噪信号进行滤波；第二步是在此基础上的改进，用了自适应的思想，及时根据当前帧的状态更新修正滤波器的系统函数，得到更精确的无噪语音信号。第三步是采用自适应LMS方法，在时域迭代计算滤波器系数，迭代次数足够多时可得到较准确的有用信号。(Implement wiener filtering used in speech enhancement. First step optimum wiener filter is obtained by using the frequency spectrum function, again to input the signal with noise filtering The second step is the improvement on the basis of this, with the idea of adaptive, and in a timely manner according to the current frame updates correction system function of the filter, get a more accurate without noise speech signal. The third step is to use the adaptive LMS method, iterative calculation in time domain filter coefficient, the number of iterations enough to get the useful signal accurately.)

基音端点检测，可用于语音识别，语音识别，和语音编码中。(speech point detection)

基于D-J阈值的加性白噪声方差估计,两种算法的比较(D-J，noise,evaluation)