PSOANN

一种music方法 对两个测量角度进行仿真分析，包括 目标个数估计和music测角(A music methods of simulation analysis, including two measuring angles of the target number of estimates and music goniometer)

matlab程序设计教程，很好的入门ppt(matlab programming tutorial, a good entry-ppt)

说明：  介绍了原子库形成及如何采用MP算法分解信号，如何用原子构造原始信号。(Describes the formation of atoms and how the library decomposition of the signal using MP algorithm, how to construct the original signal by atomic.)

ac load flow without using fact device

PSO寻优算法，能够帮助初学者学习PSO算法，并且进行实际应用(PSO optimization algorithm, PSO algorithm can help beginners learn, and practical application)

液压系统模糊自适应PID控制仿真，包含模糊控制器的设计文件。(Fuzzy Adaptive PID control of hydraulic system simulation)

认知无线电 硬判决 EGC 不同虚警概率(Cognitive radio hard decision EGC different probability of false alarm)

说明：  蒙特卡洛算法的例程，包含所需的全部相关程序(Monte Carlo algorithm routine)

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

基于最小二元树的编码传输问题，用Matlab编程求解(Binary tree coding based on minimum transmission problem, solved with the Matlab programming)