sampleEntropy

电机的机械特性图，由matlab计算以及仿真得到(Mechanical characteristics of the motor map, as well as by the matlab simulation has been calculated)

通用三次样条插值函数，可求解离散点的三次样条插值(General cubic spline interpolation function, can solve the discrete points of the cubic spline interpolation)

说明：  一个实现hilbert变换的小程序包，程序写得很简明，对理解hilbert变换的实现过程很有帮助(Hilbert transform an implementation of small packages, programs written very concise and to the understanding of the implementation process is helpful hilbert transform)

rectifier electrical converter

说明：  simulink建的模型,用于直线电机,仿真时数据要自己加入(simulink model built for the linear motor)

这是matlab宝典里面的源代码 相信对于开发着有所帮助(This is a matlab source code inside the book and I believe that the development of a help)

EMD的Toolbox及使用方法 经验模态分解（Empirical Mode Decomposition, 简称EMD）是由美国NASA的黄锷博士提出的一种信号分析方法.它依据数据自身的时间尺度特征来进行信号分解, 无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。正是由于这样的特点, EMD 方法在理论上可以应用于任何类型的信号的分解, 因而在处理非平稳及非线性数据上, 具有非常明显的优势。所以, EMD方法一经提出就在不同的工程领域得到了迅速有效的应用, 例如用在海洋、大气、天体观测资料与地震记录分析、机械故障诊断、密频动力系统的阻尼识别以及大型土木工程结构的模态参数识别方面。本工具书主要分以下几个部分：导论、非稳态信号介绍、一维时频信号分解、二维时频信号分解、时频影像信息提取等。 (Time frequency toolbox for use with MATLAB The Time-Frequency Toolbox has been mainly developed under the auspices of the French CNRS (Centre National de la Recherche Scientifique). It results from a research effort conducted within its Groupements de Recherche ”Traitement du Signal et Images” (O. Macchi) and ”Information, Signal et Images” (J.-M. Chassery). Parts of the Toolbox have also been developed at Rice University, when one of the authors (PG) was visiting the Department of Electrical and Computer Engineering, supported by NSF. Supporting institutions are gratefully acknowledged, as well as M. Guglielmi, M. Najim, R. Settineri, R.G. Baraniuk, M. Chausse, D. Roche, E. Chassande-Mottin, O. Michel and P. Abry for their help at different phases of the development.)

To find the largest fitness value and its location 寻找最大适应性及相应的位置！Population N=50；crossover bits=n/2 (half of bits of an individual) with random locations，mutation bits = 4 种群数 N=50，交换位数= n/2, 即个体位数的一半，且位置随机； 变异位数统一取为4； Nc=20，28，36，44，individuals for crossover(交换的个数)。Nm=1，5，10，15， individuals for mutation(变异的个数)。(To find the largest fitness value and its location to find the location of the maximum adaptability and the corresponding! Population N = 50 crossover bits = n/2 (half of bits of an individual) with random locations, mutation bits = 4 population size N = 50, exchange digits = n/2, ie half of the median individual, and random position variation is taken as unity median 4 Nc = 20,28,36,44, individuals for crossover (exchange number). Nm = 1,5,10,15, individuals for mutation (the number of variations.))

说明：  simulink中常见的坐标变换的模型，可直接拿来用，希望对新手有所帮助(simulink common coordinate transformation model can be directly used with the hope that help the novice)

Energy Effi cient Hierarchical Cluster-Based Routing for Wireless Sensor Networks