i_lab2lch

基于MATLAB的信号表示及运算，实现信号的反转、平移、展缩、相加和相乘。(MATLAB-based signal representation and computation, to achieve signal inversion, translation, exhibition shrinking, adding and multiplying.)

it is cluster3 matlab code

Matlab及其在信息工程中的应用，对matlab的使用进行了全面的介绍，是matlab初学者的最佳选择(Matlab and its application in information engineering, a comprehensive introduction of matlab, the best choice for beginners )

灰度拉伸是分段进行线性变换，对红色，绿色，蓝色三分量进行统一的分段线性变换，以增强图像对比度 (Gray-scale stretch is sub-linear transformation of the red, green, blue three-component unified piecewise linear transformation, to enhance the image contrast)

时频分析工具箱是基于matlab的语言设计的一种基于时频分析的信号处理方法.(Time-frequency analysis matlab toolbox is based on the language of design based on time-frequency analysis of signal processing methods.)

说明：  一个自己做的异步电动机的模型，由于是理想化模型，忽略了铁损耗。(An induction motor to do its own model, because it is idealized model, neglected iron loss.)

简单的ASR和ACR的仿真电路，运用simulink模拟，可以自行代入参数(A simple ASR and ACR circuit simulation, using Simulink simulation, can be substituted into the parameter )

用于MATLAB中潮流计算的软件包，内含使用说明和多个测试文件，使用方便(MATLAB software is used to calculate the trend, contains instructions and multiple test files, easy to use)

Seperates a dynamically input signature into different strokes.

说明：  粒子群算法(pso)标准测试函数验证程序。在一个m文件中包括了目前文献中用于验证的7个标准测试函数(Ackley等)、三维动态显示，粒子过分集中时打散等功能。旨在为学习和研究者pso算法的同仁提供一个功能较为完备、简单易懂的标准版本，对于初学者可以通过此程序快速的实现入门，以便将更多的精力投入到深层次的研究中去！同时愿与所有致力于此的朋友共同探讨pso算法的改进与应用方面(如多目标、动态系统等)的经验。(PSO algorithm (PSO) standard test function verification process. M in a document, including the current literature is used to validate the seven standard test function (Ackley), 3D dynamic display, and the over-concentration of particles scatters when the function. Designed for researchers to study and colleagues at the PSO algorithm to provide a more complete functional and easily understood standard version, for beginners through this program to achieve rapid entry. in order to be more energy into depth study! While willing to work with all the friends here to discuss PSO algorithm improvements and applications (such as multi-target, Dynamic systems, etc.) experience.)