fun

This program print electric field pattern for rectangular Aperture Antenna

车牌识别切割算法。正确定位车牌字符，然后对其进行切割。(License plate character segmentation)

signal processing using matlab

matlab6.5 Figure pattern process source program, it s better to have the books to read consulting together (matlab6.5 Figure pattern p source process rogram. it's better to have the books to read consulting t ogether)

本软件主要用于fMRI等图像数据处理，常常结合matlab分析，希望对大家有用(This software is mainly used for the fMRI image data processing, and is often combined with Matlab analysis, and hope to be useful)

说明：  基于matlab简单图像处理系统中对图片进行增强对比度的处理(Based on a simple matlab image processing system to enhance the contrast of the picture processing)

对信号进行强制去噪 默认阈值去噪和给定软阈值去噪(The signal is forced denoising the default threshold denoising and given soft threshold denoising )

反射系数与地震子波褶积合成地震记录，p，d，s分别是预设地层纵波速度、密度、及横波速度模型。其中包含可以改变主频的ricker子波，avopp是提取反射系数的程序。wigb可以对其中的多道进行强化显示。(Reflection coefficient and the convolution synthetic seismogram, the seismic wavelet p, d, s are preset formation p-wave velocity, density, and shear wave velocity model. Contains can change the frequency of the ricker wavelet, avopp is the process of the extraction of reflection coefficients. Wigb can to strengthen the multi-channel display.)

adaptive beam forming in smart antennas using rls algorithm in planar antennas

考虑两辆车在道路上同向行驶，在O-16s时，两车均保持匀速直线运动，由安装在后车上的车载毫米波雷达检测出与前车的距离为150m，相对速度为-3m/s，方位角 。在16-20s时，前车向右偏转，与后车的相对角加速度为 。后车加速，与前车的纵向相对加速度为 。雷达的扫描周期为T=0.1s，系统噪声为 ， 。量测误差为 。(Consider the two cars traveling the same direction on the road, in the O-16s, the two vehicles are kept uniform linear motion, installed in the vehicle after the car millimeter wave radar to detect the distance of the vehicle in front 150m, the relative speed- 3m/s, Azimuth. In the 16-20s, the first car to the right deflection, and the relative angular acceleration after the car is. After the vehicle acceleration, relative to the vehicle in front of the vertical acceleration. Radar scan period T = 0.1s, the system noise. Measurement error.)