canchadj

FEM 计算电磁铁周围磁场分布的程序，简洁易懂(FEM calculation of magnetic field distribution around the magnet program and easy to read)

基于matlab的数字基带系统各种调制解调链路，包括am,ssb,pcm等，对调制信号，误码率，眼图等进行了仿真(Matlab-based system, a variety of digital baseband modem link, including am, ssb, pcm, etc., on the modulation signal, the error rate, eye diagrams simulated)

文中的方法是把图像分块，小波分解得到低频分量、高频分量，然后计算每一块的对比度，把图像块划分为清晰块、模糊块，把清晰块和模糊块相邻的区域定义为边界区域，融合时，直接选取清晰块作为融合后的相应块，对于边界区域，在小波分解的基础上采用基于对比度的像素选取的方法进行处理。(Paper, the method is to image segmentation, wavelet decomposition are low frequency, high frequency components, then calculate the contrast of each piece, the image block is divided into clear blocks, fuzzy block, to clear blocks and fuzzy block is defined as the border region adjacent to area, integration time, a clear block directly select the corresponding block as a fusion, for the border region, the wavelet decomposition on the basis of the pixel-based contrast method selected for processing.)

方孔衍射的实例，方便直观学习衍射花样的性质，了解简单光调制的原理(Fang Kong diffraction)

matlab实现的粒子滤波器源代码，多若干实例并有与Kalman滤波器性能的比较(realize the particle filter matlab source code, and more with some examples and compare the performance of Kalman filter)

说明：  

说明：  自适应滤波器解决非平稳的过程，因为实际信号的统计特性可能是非平稳的或者是未知的。(Adaptive filter solves the non-stationary process, because the statistical characteristics of the actual signal may be non-stationary or unknown.)

matlab 程序求解梁单元内力，简单易学，好东西(matlab program for solving beam element internal force, easy to learn, a good thing)

saber仿真文件，开环LLC，下载后改改参数就是你自己得了(Saber simulation files, open loop LLC, download after change parameter is yourself)

MATLAB实现连续信号采样、频谱分析和采样信号恢复的方法。计算在临界采样、过采样、欠采样三种不同条件下恢复信号的误差，并由此总结采样频率对信号恢复产生误差的影响，从而验证时域采样定理。(MATLAB continuous signal sampling, spectral analysis and sampling signal recovery method. Calculated in a critical sampling, the oversampling signal error recovery due to the sampling of the three different conditions, and thereby generate error summarizes the sampling frequency for signal recovery, in order to verify the time domain sampling theorem.)