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在现代谱估计中，用自相关的无偏估计代替周期图中自相关函数的有偏估计，可能导致出现负的谱估计值，因此采用BT谱估计器的方法(In the modern spectral estimation, the use of self-related unbiased estimate the figure to replace the cycle of auto-correlation function biased estimate may lead to a negative estimated value of the spectrum, so the use of BT s method of spectral estimation)

矩形检测,基于MATLAB的利用霍夫变换，自己弄的，很实用(rectangular detection)

本代码为高阶滑模观测器的MATLAB仿真源文件，希望大家下载学习。(The code for the high order sliding mode observer of MATLAB simulation source file, hope everyone to download learning.)

说明：  一种改进的局部线性嵌入算法，性能比传统的要好(An improved local linear embedding algorithm with better performance than the traditional LLE algorithm)

基于异步分布式价格（ADP）算法的功率控制matlab仿真，利用梯度算法来达到纳什均衡，求得最优解。(Asynchronous Distributed Price (ADP) power control algorithm matlab simulation, using the gradient algorithm to achieve the Nash equilibrium, get the optimal solution.)

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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.)

基于神经网络下的《MATLAB神经网络30个案例分析》程序(Based on Neural Network under " MATLAB neural network 30 Case Studies" Program)

for using this code need to use signal toolbox and general toolbox in your matlab Using Daubechies transform to compress the image (showing remaining coefficen of Thresholded Image) and then using Inverse 2D Daubechies transform and finding the SNR to see how well decompression works

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.)