Newton

含噪的三角波和正弦三角波去噪问题，简便的程序，直接在matlab中打开即可(meaningful)

function [A,w,type,tao]=amplres(h) 《数字信号处理教程——MATLAB释义与实现》子程序 给定FIR滤波器系数求滤波器符幅特性(function [A, w, type, tao] = amplres (h) " digital signal processing tutorial- MATLAB Interpretation and Implementation" procedure FIR filter coefficients of a given symbol rate filter characteristics of demand)

ekf,扩展卡尔曼滤波，组合导航技术，是适合初级学习的资料(ekf，extended kalman filter，integrated navigation)

解耦控制要求下的极点配置Matlab算法(Decoupling control requirements under the pole placement Matlab algorithm)

The simulation is a wideband signal is white noise with variance 0.05, single frequency to the frequency of the signal for a single frequency signal 2 to 2 times the adaptive filtering simulation

hht可以实现希尔伯特黄变换，对信号进行包络分解...(code)

Matlab经典算法与程序之绘图，包括M文件和一个PPS教程(Matlab classic graphics algorithms and procedures, including the M file and a tutorial PPS)

这是研究生毕业论文做的项目——基于粒子滤波和卡尔曼滤波的卫星定位技术。附件中包含了无线信道估计和均衡、TDOA测距、IMM-KF滤波的所有程序，希望对从事无线定位技术的开发人员有帮助。独家奉献。(This is the project graduate thesis do-- Based on satellite positioning technique of particle filter and Calman filter. Annex contains all the applications of wireless channel estimation and equalization, TDOA distance, IMM-KF filter, and they hope to help in the wireless location technology development personnel. Exclusive dedication.)

基本的免疫克隆算法，可以帮组大家学习智能算法(The basic immune clonal algorithm, can help set them to learn from intelligent algorithm)

说明：  粒子群算法（PSO）是一种基于群体的随机优化技术。与其它基于群体的进化算法相比，它们均初始化为一组随机解，通过迭代搜寻最优解。不同的是：进化计算遵循适者生存原则，而PSO模拟社会。将每个可能产生的解表述为群中的一个微粒，每个微粒都具有自己的位置向量和速度向量，以及一个由目标函数决定的适应度。所有微粒在搜索空间中以一定速度飞行，通过追随当前搜索到的最优值来寻找全局最优值。 PSO模拟社会采用了以下三条简单规则对粒子个体进行操作：①飞离最近的个体，以避免碰撞。②飞向目标。③飞向群体的中心。这是粒子群算法的基本概念之一。 粒子群算法其基本思想是受许多鸟类的群体行为进行建模与仿真研究结果的启发(Particle swarm optimization (PSO) is a population based stochastic optimization techniques. Based on evolutionary algorithms compared with other groups, they are initialized to a random solution, iterative search through optimal solution. The difference is: the principle of survival of the fittest evolutionary computation to follow, while PSO simulation community. The potential of each solution expressed as a group of particles, each particle has its own position vector and the velocity vector, and a fitness determined by the objective function. All particles in the search space at a constant speed flight, by following the current search to find the optimal values ​ ​ of the global optimum. PSO simulation community has adopted the following three simple rules for the operation of individual particles: ① recently departed individuals, in order to avoid collisions. ② to the target. ③ fly to center groups. This is one of the basic concepts of particle swarm algorithm. PSO algori)