gcut

模拟在住不同条件下长周期光纤光栅的传输谱，给出了各个不同条件下传输谱的变化(Simulation under different conditions in living long period fiber grating transmission spectrum, gives the transmission spectrum under different conditions, changes in)

基础自适应均衡化利用lms或rls方法,通俗易懂,适合初学者(Adaptive equalization based on the use of LMS or rls methods, user-friendly, suitable for beginners)

小波包分析提取振动信号中的分解小波包分析提取振动信号中的分解(Wavelet packet analysis vibration signal decomposition wavelet packet analysis vibration signal decomposition)

自适应巡航控制示例，matlab代码，可运行(Adaptive Cruise Control Example)

水印嵌入 扩频算法 使用了空域算法 实现水印嵌入(Watermark embedding algorithm uses the spatial spread spectrum watermark embedding algorithm)

功率谱密度相关方法的MATLAB实现代码，包含基础讲解和算例代码(Power spectral density related methods of MATLAB code, including basic explanation and example code)

全极化SAR图像极化定标算法，适用于星载SAR，包含法拉第旋转角的校正(Polarization polarimetric SAR image scaling algorithm for spaceborne SAR, includes correction of Faraday rotation angle)

Mathematic Pascal problems. it is a lil bit easy with a triangle structure. and the number inside.

LDPC仿真程序,纠错码中的LDPC码，码长越长，纠错性能越好，是美国NASA深空通信运用的纠错编码(LDPC code for matlab)

Among the high-complexity methods, two methods dominate the literature Kalman filtering and Mixture of Gaussians (MoG). Both have their advantages, but Kalman filtering gets slammed in every paper for leaving object trails that can t be eliminated. As this seems like a possible deal breaker for many applications, I went with MoG. Also, MoG is more robust, as it can handle multi-modal distributions. For instance, a leaf waving against a blue sky has two modes—leaf and sky. MoG can filter out both. Kalman filters effectively track a single Gaussian, and are therefore unimodal: they can filter out only leaf or sky, but usually not both.