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带交叉电极的混频器中，电极的面积对THz输出功率的影响(Mixer with cross-electrode, the electrode area, the impact of the THz output power)

说明：  gpops工具箱+例子（详细注释）+官方手册(Gpops toolbox + examples (detailed comments) + official manual)

自适应滤波器--最小均方误差法LMS滤波自编程--简明易懂附有注释(Adaptive filter- the minimum mean-square error method LMS filter self-programming- easy to understand annotated)

用窗函数法设计FIR数字滤波器。包括：1.矩形窗2.三角窗3.汉宁窗4.海明窗5.布拉克曼窗6.凯泽窗等(FIR digital filter design with a window function method. Including: a rectangular window. Triangular window. Hanning Hamming window, Blackman window and Kaiser window)

matlab主要工具箱函数以及详细注解等等。(matlab toolbox function main, and detailed notes and so on.)

基本光纤组件，GUI图形界面，无内嵌函数，(Basic fiber optic components, GUI graphical interface, no built-in functions,)

nsga2与DE算法的结合算法,用于求解多目标优化问题(the combination of nsga2 algorithm with DE algorithm )

chaotic keril her optimization

说明：  实现多尺度熵的算法 多尺度熵（Multiscale entropy, MSE）将样本熵扩展到多个时间尺度，以便在时间尺度不确定时提供额外的观察视角。样本熵的问题在于它没有很好地考虑到时间序列中可能存在的不同时间尺度。为了计算不同时间尺度下信号的复杂性，Costa等人（2002,2005）提出了多尺度熵。(MultiScale Entropy There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise.)

高频系数融合均采用基于像素点绝对值取大的规则，这里要注意的是，比较的对象是两幅原始图像的像素点的绝对值，而融合后图像的像素点的取值是两幅原始图像像素点绝对值大的那一点的值，也就是说，要取绝对值大的那个点的实际值