laplacian

说明：  分析了LTE系统频率偏移，定时误差，信道估计问题等，并对广义Rake接收机和CPEDS接收机的性能做了比较。(Analysis of the LTE system frequency offset, timing error, channel estimation problems, and generalized Rake receiver performance receiver and CPEDS were compared.)

a roletwheel matlab s code

利用遗传算法的选择、交叉、变异功能来求解De Jong函数优化问题(The use of genetic algorithm selection, crossover and mutation function to solve the function optimization problem De Jong)

HSV空间 基于火焰动态特征和运动检测的火灾检测(Based on the dynamic characteristics of the flame of fire detection and motion detection)

libevent源码分析,具体的一般实现(libevent)

This file is fast background subtraction file

信噪比=20，迭代步长=0.035，本次程序设计还是验证了RLS比LMS收敛快的效果。(SNR = 20, iteration step = 0.035, this program is designed to verify the RLS faster than the LMS convergence effect.)

说明：  近年来，基于启发式的多目标优化技术得到了很大的发展，研究表明该技术比经典方法更实用和高效。有代表性的多目标优化算法主要有NSGA、NSGA-II、SPEA、SPEA2、PAES和PESA等。粒子群优化(PSO)算法是一种模拟社会行为的、基于群体智能的进化技术，以其独特的搜索机理、出色的收敛性能、方便的计算机实现，在工程优化领域得到了广泛的应用，多目标PSO(MOPSO)算法应用到了不同的优化领域[9~11]，但存在计算复杂度高、通用性低、收敛性不好等缺点。 多目标粒子群（MOPSO）算法是由CarlosA. Coello Coello等在2004年提出来的(In recent years, heuristic-based multi-objective optimization technology has been greatly developed, and research shows that this technology is more practical and efficient than classical methods. Representative multi-objective optimization algorithms mainly include NSGA, NSGA-II, SPEA, SPEA2, PAES and PESA. Particle Swarm Optimization (PSO) algorithm is an evolutionary technology based on swarm intelligence that simulates social behavior. With its unique search mechanism, excellent convergence performance, and convenient computer implementation, it has been widely used in the field of engineering optimization. The objective PSO (MOPSO) algorithm is applied to different optimization fields [9~11], but it has shortcomings such as high computational complexity, low versatility, and poor convergence. The multi-objective particle swarm optimization (MOPSO) algorithm was proposed by Carlos A. Coello Coello et al. in 2004)

Run RGB Video and watch the R-G-B Video Components parralel to the original Video

Implementation of the extended Euclidean algorithm for polynomials over GF(2^m