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语音减噪，自适应滤波器减噪，谱减法减噪，维纳滤波法减噪等(Voice noise reduction, the adaptive filter, noise reduction, and reduce the noise spectrum subtraction, wiener filtering method of noise reduction, etc)

处理信号的时频分析，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，最小均方误差（MMSE）的算法。( When processing a signal frequency analysis, Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm, Minimum mean square error (MMSE) algorithm.)

绘制苯环的matlab源文件，对于精确绘图有一定的价值(Drawing phencynonate the matlab source file, for AccuDraw a certain value)

MATLAB神经网络30个案例分析—案例28 灰色神经网络的预测算法—订单需求预测源代码及数据(MATLAB Neural Network 30 Case Studies- Case of 28 gray neural network prediction algorithm- order demand forecast source code and data)

Implement chip controller for a composite microgrid.

Speech Recognition with Tdnn by simulink

matlab中结合小波和偏度对故障信号的处理(matlab combination of wavelet and skewness of the fault signal processing)

switching median filter for removing impulse noise

主要作为初学者对matlab界面设计，非常经典(主要作为初学者对matlab界面设计)

利用SVM做回归线性测试。对于大盘指数的有效预测可以从整体上观测股市的变化提供强有力的信息，所以对上证指数的预测很有意义。通过对上证指数从1990.12.20-2009.08.19每日的开盘数进行回归分析，最终拟合的结果是：均方误差MSE=2.35705 e-005，平方相关系数 R=99.9195 。SVM的拟合结果还是比较理想的。(Make use of SVM linear regression testing. For the market index can predict the observed changes in the stock market as a whole to provide a strong information, so it makes sense to predict the Shanghai index. Through the Shanghai Composite Index opened daily from 1990.12.20-2009.08.19 number of regression analysis, the results of the final fit are: mean square error MSE = 2.35705 e-005, the square of the correlation coefficient R = 99.9195 . SVM fitting result is quite satisfactory.)