radar1

迭代crc,用于drom的crc校验，参数可以自己更改。(Iterative crc, crc check for drom the parameters can be changed.)

关于相控阵雷达的经典书籍，对学习雷达相当有帮助(On the phased array radar on the classic books, for learning radar quite helpful)

实现QAM调制解调，分为16QAM、64QAM，包括瑞利信道的仿真程序，可以供初学参考。(Implementation of QAM modulation and demodulation, divided into 16QAM, 64QAM, including Rayleigh channel simulation program, can be reference for beginners.)

This matlab code for DWT image watermarking

Convinieng tool to use weka in matlab.

此代码仿真了一个语音输入输出系统，语音信号经过AD转换后，经过DSSS调制解调后，通过DA转换还原输入的声音，每一步的的波形都可以观测，对实际DSSS系统设计有很大的参考价值(This code simulation of a voice input and output systems, speech signal after AD conversion after DSSS modem through DA conversion to restore the input voice, each step of the waveform can be observed, the actual design of DSSS systems have great reference value)

Function reconstructs an estimate of a surface from its surface normals by correlating the surface normals with that those of a bank of shapelet basis functions. The correlation results are summed to produce the reconstruction. The sumation of shapelet basis functions results in an implicit integration of the surface while enforcing surface continuity. Note that the reconstruction is only valid up to a scale factor (which can be corrected for). However the reconstruction process is very robust to noise and to missing data values. Reconstructions (up to positive/negative shape ambiguity) are possible where there is an ambiguity of pi in tilt values. Low quality reconstructions are also possible with just slant, or just tilt data alone. However, if you have full gradient information you are better off with the Frankot Chellappa algorithm below.

说明：  遗传算法和BP神经网络组合，风速的超短期预测(The combination of genetic algorithm and BP neural network can predict wind speed)

基于偏微分方程的多级分层的图像增强算法，(Multi-level hierarchical image enhancement algorithm based PDE algorithm)

matlab编写实现NEC编码，结合任意波形发生器，采样率50K(matlab prepared to achieve NEC coding, combined with an arbitrary waveform generator, sample rate 50K)