Animated_GIF

利用传输线模型，结合时域有限差分法（FDTD）思想，分析传输线终端响应(Using transmission line model, combined with finite difference time domain (FDTD) idea of ​ ​ the transmission line terminal response)

掺铒浓度与小信号增益的关系 掺铒浓度与光纤长度的关系(Erbium-doped concentration and the relationship between small-signal gain)

高炜炳老师1996年写的变结构控制的经典书籍，有助于学习变结构相关的内容(sliding model control of nonlinear system control)

The fusion of high-spectral/low-spatial resolution multispectral and low-spectral/high-spatial resolution panchromatic satellite images is a very useful technique in various applications of remote sensing. Recently, some studies showed that a wavelet-based image fusion method provides high quality spectral content in fused images. However, most wavelet-based methods yield fused results with spatial resolution that is less than that obtained via the Brovey, IHS, and PCA fusion methods. In this paper, we introduce a new method based on a curvelet transform, which represents edges better than wavelets. Since edges play a fundamental role in image representation, one effective means to enhance spatial resolution is to enhance the edges. The curvelet-based image fusion method provides richer information in the spatial and spectral domains simultaneously. We performed Landsat ETM+ image fusion and found that the proposed method provides optimum fusion results.

This is a code of Pseudo-Arc Length Continuation Method , the method can be used for solving the nonlinear equations, the principle can re found in some text books. In the code,I prove the agreement of the code with other methods

图像处理之中的对已经预滤波的信号进行多小波分解的Matlab实验程序(Image processing are already pre-filtering of the signal decomposition Matlab Multiwavelet experimental procedures)

使用matlab软件修改文件名，可以一次性修改很多歌文件名字(Use matlab software to modify the file name)

对白噪声的谱熵进行了计算。大家可以参考一下，(Spectrum Entropy )

二维TM模电磁波FDTD仿真，UPML边界(2D TM electromagnetic FDTD simulation, UPML border)

t - time series y - value of series at time t w - cycle length, defined by user based on prior knowledge of time series alpha - type I error used for cofidence interval calculations. Usually set to be 0.05 which corresponds with 95 cofidence intervals(t- time series y- value of series at time t w- cycle length, defined by user based on prior knowledge of time series alpha- type I error used for cofidence interval calculations. Usually set to be 0.05 which corresponds with 95 cofidence intervals)