2nd

space-time adaptive processing (STAP)

修改自wiley的书中的各种遗传算法（GA）matlab代码，还包括其他一些算法如粒子群优化，蚁群优化等，均已修改好用！(Modified since the book wiley various genetic algorithms (GA) matlab code, also includes a number of other algorithms such as PSO, ant colony optimization and so on, have been modified handy!)

这个Constriction pso 界面提供了10个可选择的测试函数，在界面可以输入粒子数和维度以及迭代次数，同时界面将输出全局最优和得到当前最优所需的迭代次数。里面有一个ＴＸＴ文档有一些操作说明；(The Constriction pso interface provides 10 selectable test function, can enter the number of particles in the interface and the dimensions and the number of iterations, while the output interface to get the current global optimum and the optimal number of iterations required. There is a TXT document some of the instructions )

这是基于互信息的图像配准程序，实现起来比较简单，是用matlab实现的(This is based on mutual information image registration procedure is relatively simple to achieve them, is achieved using matlab)

此算法先把伤病人员进行特殊对待，在计算出其他人的入院日期，表二的出院日期为 统计的期望值 运用是要改变 数据的初值 和u值（数据录入个数）；(This algorithm first special treat the sick and wounded, in the calculation of other people' s admission date, discharge date in Table II used for the statistical expectation is to change the initial data and u values ​ ​ (the number of data entry) )

牛顿法,用于优化求解，在图像优化求解,在点散射目标的仿真 (newton)

ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。 基本思想： 在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。 (Description This is an example of the basic Active Shape Model (ASM) as introduced by Cootes and Taylor, with multi-resolution approach. Basic idea: The ASM model is trained from manually drawn contours in training images. The ASM model finds the main variations in the training data using Principal Component Analysis (PCA), which enables the model to automatically recognize if a contour is a possible/good object contour. Also the ASM models contains covariance matrices describing the texture of the lines perpendicular to the control points when in the correct positions. After creating the ASM model, an initial contour is deformed by finding the best texture match for the control points. This is an iterative process, in which the movement of the control points is limited by what the ASM model recognizes from the training data as a "normal" object contour. Literature: - Ginneken B. et al. "Active Shape Model Segmentation with Optimal Features", IEEE Transactions on Medical I)

direct matrix inversion algorithm matlab code

Energy Effi cient Hierarchical Cluster-Based Routing for Wireless Sensor Networks

simulink滤波率仿真 二阶和四阶低通滤波(filtering rate simulation simulink second and fourth-order low-pass filter)