Phased-array-imaging

模糊神经网络解耦的MATLAB程序，适用于神经网络学习者(MATLAB fuzzy neural network decoupling procedures applicable to the neural network learners)

采用simulink搭建的BPSK调制解调模块(Simulink built using BPSK modulation and demodulation modules)

摄像机的标定、角点的提取、三维空间的重建、最后生成矫正后无畸变的图形(Camera Calibration，This section takes you through a complete calibration example based on a total of 20 (and 25) images of a planar checkerboard. This example lets you learn how to use all the features of the toolbox: loading calibration images, extracting image corners, running the main calibration engine, displaying the results, controlling accuracies, adding and suppressing images, undistorting images, exporting calibration data to different formats... This example is highly recommended for someone who is just starting using the toolbox. )

基于BPSK调制的认知无线电能量检测,关于检测概率和虚警概率(bpak modulation for energy detection base on CR)

滚动轴承故障诊断 小波包分解 峭度最大尺度重构(Roller Bearing Fault Diagnosis Based on Wavelet Packet Decomposition kurtosis largest scale reconstruction)

matlab 视频序列连续抽帧处理(matlab from vedio get frame )

In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle s position and velocity. Each particle s movement is influenced by its local best known position and is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expected to move the swarm toward the best solutions.

Kalman滤波元模块代码，可调用扩展为更为复杂的程序。(Kalman filter element module code, call the extension for more complex procedures.)

一个利用matlab做的雷达跟踪的kalman滤波的源程序(Using matlab to do a radar tracking of the kalman filter source code)

对于频率估计有效的研究方法 其中有matlab的原始的程序(Frequency estimation matlab)