SpeedLimitRecognition

基于FFT谱连续细化算法的高精度频率估计，这种算法可以精确到小数点后两位，这种算法与MUSIC法和ESPRIT法相比，计算量大大降低，而且精度非常高。(This procedure is based on the FFT spectrum continual refinement algorithm s high accuracy frequency， this algorithm may precisely to decimal point latter two, compared the MUSIC algorithm and the ESPRIT algorithm, the computation complexity reduces greatly, moreover the precision is high.)

伪彩色增强,对灰度图像Fig5.bmp中不同灰度值的区域赋予不同的颜色，使生成的伪彩色图像尽可能接近现实状况。(Pseudo-color enhanced gray-scale image of gray value Fig5.bmp different regions to give a different color, so that the resulting pseudo-color image as close to reality.)

This is a matlab code for BPSK, 16QAM and 32QAM demodulation

The function impulsive_noise generates non-gaussian noise with inputs of beta, gamma,and the power of noise is 1 in W or 0 in dB. The noise can be defined either real or complex. The other functions generate QAM symbol and insert a vector to another vetor with specific locations

基于MATLAB的fastica算法的实现,有完整源代码。这是一个关于盲源分离独立成分分析方法fastICA的软件包，给大家分享一下，完整的matlab代码。(MATLAB-based fastica algorithm, a complete source code. This is a blind source separation independent component analysis (ICA) of the package, to share with you, complete matlab code.)

Histogram equalization. Is a method in image processing of contrast adjustment using the image s histogram. This method increase the contrast of the example s image, because it s a image represented by close contrast values.

print & generate barcode

包含飞行器飞行中的姿态控制，如侧滑角，倾斜角，滚转角，俯仰角，添加噪声处理，基于chebyshev的水声信号分析。( It comprises aircraft flight attitude control, such as slip angle, tilt angle, roll angle, pitch angle, Add noise processing, Based chebyshev underwater acoustic signal analysis.)

说明：  基于LCL并网逆变器pq控制的matlab仿真(PQ control based on LCL grid-connected inverter)

Extended Kalman Filter Tracking Object in 3-D(Assume that we want to track an object moving in 3-D space with constant velocity. Our instruments observe bearing, range and high(cylindrical coordinates). However, of an interest are rectangular coordinates. Since transformation is non-linear this requires use of extended Kalman filter. Because transformation is non-linear between X,Y and Range,Bearing and linear between Z and high(Z is height), this problems serves as a good comparason of how well extended Kalman filter can perform. By comparing its linear estimation error in Z to non-linear estimations in X and Y, we can judge how non-familiarities effect estimation. )