ANewAdvancedGeneticAlgorithmfor

用时间序列分析中的自适应滤波预测法,建立某市用电量的预测模型 (Using time series analysis of adaptive filtering prediction method, a city electricity consumption forecasting model)

matlab圆滑曲线及曲面程序，有效去除作出的曲线和曲面的锯齿(matlab program sleek curves and surfaces, effectively removing jagged curves and surfaces )

说明：  在DOS下一个VGAL库的源程序。用TC3进行编译成功。(DOS VGAL a library of the source. Compiled with TC3 success.)

y_compare= 1.0954 1.1832 1.2649 1.3416 1.4142 1.4833 1.5492 1.6125 1.6734 1.7321 1.0954 1.1832 1.2649 1.3416 1.4142 1.4832 1.5492 1.6125 1.6733 1.7321 var_y=2.1742e-010 精度再上一个层次(三阶代数精度) (y_compare = 1.0954 1.1832 1.2649 1.3416 1. 4142 1.4833 1.5492 1.6125 1.6734 1.7321 1.0954 1.1832 1.2649 1.3416 1.4142 1.4832 1.5492 1.61 25 1.6733 1.7321 var_y = 2.1742e-010 precision on a level again ( Third-order algebraic precision))

模拟信号的数字传输系统 matlab PCM编译码技术(The analog signal of the digital transmission system)

采用RGB模型进行阴影的检测与去除。能够显示前景、背景、去除阴影后的运动目标(RGB model with shadow detection and removal. To show foreground, background, after the removal of shadows moving target)

自己总结的MATLAB命令，很实用，尤其是搞数值计算时候！(Own summary of the MATLAB command, it is useful, especially when engaged in numerical calculation!)

this simulation is a way for watermarking and steganography with HUGO

利用MATLAB程序编写的语音识别系统界面，很经典(Using MATLAB programming speech recognition system interface, very classic)

说明：  最小均方濾波器是一類可通過最小化誤差訊號之均方值而修正濾波器係數，以類比所需理想濾波器的自適應濾波器，其中作為修正依據的誤差訊號為理想參考訊號與實際輸出訊號之差。該種濾波器所用之最小均方法只以當前之訊號誤差值為準進行修正，是一種隨機梯度下降法。最小均方法係由斯坦福大學的Bernard Widrow教授及他的首位博士班學生Marcian Hoff於1960年提出。最小均方濾波器屬於常見的自適應濾波器種類之一。(The minimum mean square filter is an adaptive filter that can correct the filter coefficients by minimizing the mean square value of the error signal to analogize the desired ideal filter. The error signal used as the correction reference is the ideal reference signal and the actual output. The difference between the signals. The minimum averaging method used in this kind of filter is only corrected based on the current signal error value, which is a stochastic gradient descent method. The minimum mean method was proposed in 1960 by Professor Bernard Widrow of Stanford University and his first PhD student, Marcian Hoff. The least mean square filter is one of the common types of adaptive filters.)