mohinh_Thay1

1.掌握图像滤波的基本定义及目的； 2.理解空域滤波的基本原理及方法； 3.掌握进行图像的空域滤波的方法。 (1. Image filtering grasp the basic definition and purpose; 2. Understanding of spatial filter the basic principles and methods; 3. master images of the spatial filter method.)

用双线型描述系统，并且使系统的模型具有良好的鲁棒性(Described by bilinear system, and the system model has good robustness)

remote sensing 112313

Telnet Connect Server Application in C#, Visual Studio 2010

迭代自组织数据分析，是本科毕设的题目，使用高阶累积量对MPSK信号进行调制识别。( Iterative self-organizing data analysis, The title of the commercial is undergraduate course you Using high-order cumulants of MPSK signal modulation recognition.)

资源描述从数理统计的观点看，这里涉及的都是随机变量，我们根据一个样本计算出的那些 系数，只是它们的一个（点）估计，应该对它们作区间估计或假设检验，如果置信区间 太大，甚至包含了零点，那么系数的估计值是没有多大意义的。另外也可以用方差分析 方法对模型的误差进行分析，对拟合的优劣给出评价。简单地说，回归分析就是对拟合 问题作的统计分析。 具体地说，回归分析在一组数据的基础上研究这样几个问题： （i）建立因变量 y与自变量x , x , , xm 1 2 L 之间的回归模型（经验公式）； （ii）对回归模型的可信度进行检验； （iii）判断每个自变量x (i 1,2, ,m) i = L 对 y 的影响是否显著； （iv）诊断回归模型是否适合这组数据； （v）利用回归模型对y 进行预报或控制。

create new based on mean and variance of the each cluster

使用人工势场法实现避障的无人车路径规划，且具有较多注释说明(Artificial potential field method is used to realize obstacle avoidance path planning of unmanned vehicle, which has many explanatory notes)

粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有Eberhart博士和kennedy博士发明。源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域(Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), has Dr. Eberhart and Dr. kennedy invention. Deriving from the behavior of birds of prey PSO with genetic algorithm is similar to an iterative optimization-based tools. System initialization for a group of random solutions, through the iterative search for optimal values. But there is no cross-genetic algorithm used (crossover) and mutation (mutation). But the particles in the solution space of the particles to follow the optimal search. In detail the steps after the introduction sections compared with the genetic algorithm, PSO has the advantage of being simple and easy and did not realize many of the parameters need to be adjusted. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications)

说明：  我的matlab小作业，请各位同行多多指教(my Matlab small operations, please peer exhibitions)