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说明：  优化理论与方法的黄金分割法matlab程序(Optimization Theory and Methods of golden section method matlab program)

讨论匹配滤波器对不同形式的PAM信号进行接收的情况。并研究在高斯白噪声环境中传输的改善程度(Discussion of the matched filter for different forms of PAM signal reception conditions. And to study the white Gaussian noise environment in the improvement of transmission)

LPC speech recognition

利用幂法反幂法等进行程序运算,可以获得各种适用结果.(The use of anti-power-law power-law to carry out procedures such as computing, access to a variety of application of the results.)

遗传算法解带约束的最优问题的matlab程序，适合进行遗传算法的学习(Genetic algorithm for constrained optimization problem matlab program, suitable for studying genetic algorithm)

MATLAB插值与数据拟合、样条插值与数值微积分、由已知数据拟合数学模型、信号分析与数字信号处理基础(MATLAB interpolation and data fitting, spline interpolation and numerical calculus, from the known data fitting mathematical model, signal analysis and digital signal processing-based)

控制器参数整定问题 化工过程的控制器设计加热炉控制(Controller parameter tuning problem of controller design for chemical process control furnace)

基于matlab的lorentz方程混沌运动的仿真(chaos simulation)

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(（Evolu2tionary Algorithm - EA）。PSO 算法属于进化算法的一种，和遗传算法相似，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。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years ((Evolu2tionary Algorithm- EA) .PSO algorithm is an evolutionary algorithm, and similar genetic algorithm, it is also starting random solutions, through iterative search for the optimal solution, which is also uated by the quality of the fitness solution, but it is much simpler than genetic algorithms rule, it does not have the genetic algorithm cross (Crossover) and variant (Mutation) operation, which by following the current search to find the optimal value to the global optimum. the algorithm for its easy implementation, high accuracy, and fast convergence advantages attracted academic attention, and in solving practical problems demonstrated its superiority.)

本程序为空间MIMO建模仿真程序，为MIMO信道建模的必备资料 (This procedure for MIMO spatial modeling and simulation procedures, applies to Spatial channel model for Multiple Input Multiple Output (MIMO) standard for modeling MIMO channel information required)