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粒子群优化算法（PSO）是一种进化计算技术（evolutionary computation）,由Eberhart博士和kennedy博士于1995年提出 (Kennedy J，Eberhart R． Particle swarm optimization．Proceedings of the IEEE International Conference on Neural Networks．1995．1942~1948.)。源于对鸟群捕食的行为研究。粒子群优化算法的基本思想是通过群体中个体之间的协作和信息共享来寻找最优解． (Particle Swarm Optimization (PSO) is an evolutionary computation techniques (evolutionary co mputation) by Dr. Eberhart and kennedy Dr. raised in 1995 (Kennedy, J., Eberhart R. Particle swarm optimization.Proc eedings of the IEEE International Conference o n Neural Networks.1995.1942 ~ 1948.) . From the flock of the predatory behavior. PSO algorithm is the basic idea of individual groups through the sharing of information and collaboration to find the optimal solution.)

MATLAB的一些经典使用案例 适合初学者掌握MATLAB的使用技巧(the use of MATLAB)

gauss seidal method powersystem

适用于需要用matlab环境，用som方法解决分类问题的朋友们(Applicable to the need to use matlab environment, used to solve classification problems som friends)

关于压缩感知理论的测量矩阵和重构算法分析！(Measurement matrix and reconstruction algorithm about CS)

计算有一个序列数据的线性相关系数.里面调用了MATLAB内置corrcoef函数，对取数据的序列自动处理(computing line-correlation coefficient with no interp)

说明：  传热学——热传导 一维非稳态导热微分方程画图(HEAT TRANSFER-HEAT CONDUCTION Drawing of one-dimensional unsteady heat conduction differential equation)

这是一个实现Levenberg-Marquardt算法的MATlAB代码，总共4个文件f.m产生目标评价函数，l_m_trust.m是进行L_M算法迭代处理，trtestlm.m是采用置信域方法决定更新参数和置信系数，而测试函数入口时test_lm.m，每个函数里面有详细的中文注释，希望能给你的工作带来帮助！(This is an implementation of Levenberg-Marquardt algorithm MATlAB code, generated a total of four documents fm objective evaluation function, l_m_trust.m is iterative processing algorithm for L_M, trtestlm.m Confidence region method is used decided to update the parameters and confidence coefficient and the test function entrance test_lm.m)

面阵中二维角度估计 Unitary -ESPRIT算法MATLAB程序(Two-dimensional planar array angle estimation algorithm based on MATLAB program Unitary-ESPRIT)

阻尼牛顿法求解minf(x)=(1-x1)^2+2*(x2-x1^2)^2初始点x=(0,0)精度为0.01。可运行出结果,程序清晰,算法明确。(Damped Newton method for solving min f (x) = (1-x1) ^ 2+2* (x2-x1 ^ 2) ^ 2 the initial point x = (0,0) accuracy of 0.01.It Can run out the results 。 the program is clear, algorithm is explicit. )