搜索资源列表
Discrete_PSO_TSP_C
- 离散粒子群算法（Discrete PSO）C语言源代码。 附带有利用D-PSO解决旅行商问题(TSP)的代码可作为使用时的Demo参考-discrete particle swarm algorithm (Discrete PSO) C language source code. Incidental use of a D-PSO solve the traveling salesman problem (TSP) code can be used as a reference when t
s-hanshu
- PID控制器的参数自适应，需要整定P，I ，D， 此S函数用的是固定步长，并用后向差分离散化。其中Tsa是Simulink的仿真一个周期的时间。在对图 7所示单闭环调速控制系统的动态结构图，在有自适应控制情况下，进行基于PSO算法的PID参数整定时，这个函数也会用到。
测试PSO算法的新的组合测试函数
- Novel Composition Test Functions for Numerical Global Optimization func_test.m is the main program, a basic PSO algorithm PSO_func.m is attached. SIS_novel_func.m is the function program,including six composition functions f=SIS_novel_func(x,f
BasedonprincipalcomponentanalysisoftheFaceRecognit
- 在特征提取阶段，研究了PCA, 2DPCA, (2D) 2PCA, DiagPCA, DiagPCA-F-2DPCA等多 种方法。不同于基于图象向量的PCA特征提取，由于2DPCA, (2D) ZPCA, DiagPCA和 DiagPCA-I-2DPCA的特征提取都直接基于图象矩阵，计算量小，所以特征的提取速度明 显高于PCA方法。-In the feature extraction stage, the study of the PCA, 2DPCA, (2D) 2PCA,
pso
- pso-matlab7.0例子pso(alfaB,yB,alfaN,HBB,HBN,yN,d)-pso-matlab7.0pso(alfaB,yB,alfaN,HBB,HBN,yN,d)
PSO
- 经典粒子群算法，经过多次优化，演示出图， 待优化的目标函数：N 粒子数目：N 惯性权重：w 学习因子：c1,c2 最大迭代次数：M 问题的维数：D 目标函数取最小值时自变量值：xm 目标函数的最小值：fv-Classical particle swarm algorithm, optimized for many times, demonstrates plotting objective function to be optimized: N of
LNCPSO
- 希望给辛苦科研的人带来一点点帮助--学习因子可以变化的PSO算法，不再是c1=c2=2，粒子进化更加灵活，下面是学习因子同步变化的pso，调用形式为[xm,fv]=LNCPSO(fitness,N,cmax,cmin,w,M,D)-People who want to work hard to bring a little bit of research to help- learning factor can vary PSO algorithm is no longer c1 = c2 =
tunning-PID-use-PSO
- 用pso算法优化PID参数，程序中只是对P和D的参数进行了优化-PID parameter optimization using pso algorithm, the program only the P and D parameters were optimized.
PSO_0.3-1.bin
- This document introduces the Particle Swarm Optimization (PSO) in Scilab. The PSO method, published by Kennedy and Eberhart in 1995, is based on a population of points at first stochastically deployed on a search field. Each member
PSO-0.3-1-src
- This document introduces the Particle Swarm Optimization (PSO) in Scilab. The PSO method, published by Kennedy and Eberhart in 1995, is based on a population of points at first stochastically deployed on a search field. Each member
PSO
- 标准粒子群算法的实现思想基本按照粒子群算法(2) 标准的粒子群算法的讲述实现。主要分为3个函数。第一个函数为粒子群初始化函数 InitSwarm(SwarmSize......AdaptFunc)其主要作用是初始化粒子群的粒子，并设定粒子的速度、位置在一定的范围内。本函数所采用的数据结构如下所示： 表ParSwarm记录的是粒子的位置、速度与当前的适应度值，我们用W来表示位置，用V来代表速度，用F来代表当前的适应度值。在这里我们假设粒子个数为N，每个粒子的维数为D。-His though
PSO
- 实现基于PSO的三维图形的极值计算，并显示中间的搜索过程。-Implementation is based on PSO to calculate the extremum of 3 d graphics and display in the middle of the search process.
qhbiekrn
- 基于分段非线性权重值的Pso算法，有PMUSIC 校正前和校正后的比较，旋转机械二维全息谱计算，加入重复控制，DC-DC部分采用定功率单环控制，LDPC码的完整的编译码。- Based on piecewise nonlinear weight value Pso algorithm, A relatively before correction and after correction PMUSIC, Rotating machinery 2-d holographic spectrum ca
jrvibwfb
- 对于初学matlab的同学会有帮助，Relief计算分类权重，基于分段非线性权重值的Pso算法，直线阵采用切比学夫加权控制主旁瓣比，D-S证据理论数据融合，主要是基于mtlab的程序。-Matlab for beginner students will help, Relief computing classification weight, Based on piecewise nonlinear weight value Pso algorithm, Linear array using c
hnagpzma
- 一种流形学习算法（很好用），旋转机械二维全息谱计算，多目标跟踪的粒子滤波器，采用加权网络中节点强度和权重都是幂率分布的模型，最小均方误差（MMSE）的算法，基于分段非线性权重值的Pso算法。-A fluid manifold learning algorithm (good use), Rotating machinery 2-d holographic spectrum calculation, Multi-target tracking particle filter, Using weig
csqmrnix
- 采用的是脉冲对消法，时间序列数据分析中的梅林变换工具，基于分段非线性权重值的Pso算法，有信道编码，调制，信道估计等，旋转机械二维全息谱计算，有较好的参考价值。- It uses a pulse of consumer law, Time series data analysis Mellin transform tool, Based on piecewise nonlinear weight value Pso algorithm, Channel coding, modulation, c
umkbiwjw
- 相关分析过程的matlab方法，加入重复控制，MIMO OFDM matlab仿真,D-S证据理论数据融合，基于分段非线性权重值的Pso算法，有循环检测，周期性检测。- Correlation analysis process matlab method, Join repetitive control, MIMO OFDM matlab simulation, D-S evidence theory data fusion, Based on piecewise nonlinear weigh
wvsrkxyf
- 解耦，恢复原信号，包括随机梯度算法，相对梯度算法，主要是基于mtlab的程序，旋转机械二维全息谱计算，基于分段非线性权重值的Pso算法。- Decoupling, restore the original signal, Including stochastic gradient algorithm, the relative gradient algorithm, Mainly based on the mtlab procedures, Rotating machinery 2-d holo
sietun
- 基于K均值的PSO聚类算法,D-S证据理论数据融合，有借鉴意义哦。- K-means clustering algorithm based on the PSO, D-S evidence theory data fusion, There are reference Oh.
PSO-rbf-kmeans
- pso rbf k-means simulik with matlab(programme d'un pso en hybride avec un rbf)