Mature_image_4

可以实现模式识别领域的数据的分类及回归，PLS部分最小二乘工具箱,DC-DC部分采用定功率单环控制，GPS和INS组合导航程序，主要为数据分析和统计，在MATLAB中求图像纹理特征，快速扩展随机生成树算法。( You can achieve data classification and regression pattern recognition, PLS PLS toolbox, DC-DC power single-part set-loop control, GPS and INS navigation program, Mainly for data analysis and statistics, In the MATLAB image texture feature, Rapid expansion of random spanning tree algorithm.)

图像分析和识别中一个关键的内容就是图像参数的量测，本程序可实现一些参数的量测。( In the image analysis and the recognition an essential content is the picture parameter 閲忔祴, this procedure may realize some parameters 閲忔祴. )

最大似然（ML）准则和最大后验概率（MAP）准则，BP神经网络用于函数拟合与模式识别，多目标跟踪的粒子滤波器。( Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, BP neural network function fitting and pattern recognition, Multi-target tracking particle filter.)

The sourcecode of Universally-Convergent Squared-Operator Iteration Methods for fig3 using MSOM

window 下的lua源码，值得学习,欢迎大家一起学习，下载(lua source window down, it is worth learning, welcome everyone to learn together, to download)

此matab函数文件可以用来计算模型的李雅普诺夫指数，用于稳定性分析。(this Lyapunov.m file can be used to compute the lyapunov exponential)

说明：  基于MIMO-OFDM的通信系统仿真，带注释。(Communication system simulation based on MIMO-OFDM, with notes.)

粒子群算法简介，标准的粒子群算法，标准粒子群算法的实现，MATLAB代码(Introduction of the particle swarm algorithm, the standard particle swarm algorithm, the standard particle swarm algorithm to achieve the MATLAB code )

active and apparent power

本文件对PID参数kp,ki,kd进行寻优，以ITAE作为指标函数。 PSO 文件中有详细的参数设置和寻优过程 GA寻优与PSO寻优作为对比出现 figure1展示了随着迭代次数的变化，适应度函数的收敛情况 figure2展示了kp,ki,kd的迭代情况 ht 文件是用来画图的 问题解决思路.pdf 简要介绍了粒子群算法寻优的过程(In this document, the PID parameters KP, Ki, KD are optimized, and ITAE is used as the index function. PSO file has detailed parameter settings and optimization process GA optimization and PSO optimization as a contrast appear Figure1 shows the convergence of fitness function as the number of iterations changes Figure2 shows the iterations of KP, Ki, and KD The HT file is used for drawing The problem solving idea.Pdf briefly introduces the process of particle swarm optimization)