Image_Registration_Toolbox

802.16的信道建模和仿真，在Matlab上的原代码(802.16 channel modeling and simulation in Matlab on the original code)

matlab 采用OTSU方法实现灰度图像二值化(OTSU method using gray image binarization)

MMC的模型预测控制，生成PWM调制信号主程序(MMC model predictive control, generating PWM modulation signal main program)

说明：  MATLAB code forOrdinary differential equation

绘制3层正弦信号，对之进行小波分解（5层）重构5层逼近信号和细节信号。(Draw 3-layer sinusoidal signals, the wavelet decomposition (5 layer) Reconstruction of 5-layer approximation signal and detail signal.)

针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷 入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。 该方法考虑了图像中像素点灰度􀀂 􀀂 􀀂 邻域灰度均值对作为阈值对图像进行分割 利用混沌运 动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜 索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索 时间, 提高了收敛率。(Calculation of its large capacity and particle swarm algorithm is easy to fall to strike the best threshold for the two-dimensional entropy image segmentation method Into the local optimum and slower, the proposed two-dimensional entropy image segmentation method based on chaotic particle swarm optimization algorithm. The method takes into account the image pixel the gray 􀀂 􀀂 􀀂 neighborhood average gray value as a threshold for image segmentation chaotic transport Dynamic randomness, ergodicity and initial value sensitivity of chaotic particle swarm optimization algorithm with the threshold method in two-dimensional space for the global search On request. Experimental results show that the entropy method of image segmentation method based on chaotic particle swarm optimization algorithm for threshold optimization to reduce the search Time and improve the convergence rate.)

this package is very useful. for those student doing project in ns2 software it is very helpful

说明：  基于负熵的ICA算法，独立成分分析；负熵；盲信号分离；固定点(Negative entropy based ICA algorithm, independent component analysis negative entropy blind signal separation fixed point)

landweber是一种代数重建算法，相对别的算法，它的重建速度较快，用于图像重建等(landweber is an algebraic reconstruction algorithm, compared to other algorithms, it is faster to rebuild, for image reconstruction)

Kai Borre的很经典的计算卫星位置的代码(Classic computing satellite positions Kai Borre code)