protection

2011年秋季 北京航空航天大学惯性导航原理第二次大作业(2011 inertial navigation the second homework of beihang university )

Edge detection that detect the side of object

Optimal point for brain function

核方法工具箱，包括核典型相关分析KCCA，KPLS等算法的源码和实现。(Kernel Methods Toolbox KMBOX includes implementations of algorithms such as kernel principal component analysis (KPCA), kernel canonical correlation analysis (KCCA) and kernel recursive least-squares (KRLS). )

A MATLAB code for fingerprint enhancement.

matlab开发的FIR滤波器，附音频，效果良好(matlab developed FIR filter, with audio, the effect of good)

kalman这个著名模型在图像处理与机器智能方面的应用的一些代码，打包上传了，基于matlab平台开发的。(Tracking the famous model in image processing and machine intelligence and the application of some code, Upload the package, based on the Matlab development platform.)

用振幅为0.8的方波进行傅里叶分析，并求当K不同值时的合成信号。(By amplitude of 0.8 square wave to Fourier analysis, and pray for different value when K synthetic signal. )

simulink自适应程序s函数和模型，可以用到噪声控制等方向(simulink adaptive program s functions and models, and so can be used to control the direction of the noise)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm.)