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AR模型,用经典法的自相关法求谱估计，简单实用(AR model, using the classic method of auto-correlation spectral estimation method, simple and practical)

说明：  一个多分类支持向量机的文件，可直接运行，并且可以多数据进行多重分类，十分好用(A multi-class support vector machine files can be directly run, and can make multiple multiple data classification, is very easy to use)

关于谱分析的一些算法，其中包括周期图法、Blackman-Turkey法、Yule-Walker方程求解、最小二乘AR、最小二乘ARMA、ESPRIT、MUSIC、Root-MUSIC、Capon、和AIC准则等等经典算法。(Classical algorithm on Spectral Analysis, including periodigram, Blackman-Trukey, Yule-Walker,LSAR, LSARMA,ESPRIT, MUSIC, Root-MUSIC, Capon, AIC and so on.)

说明：  page变换例程，可以对信号进行柯恩类时频分布中的page变换(page conversion routines, you can type on the signal time-frequency distribution of Cohen)

This function helps you to find moments from an Image

UN AUTRE MONDE DE LA VISION.............MATLAB..................SEGMENTATION

一个MATLAB/Simulink模型，关于电动汽车动力电池荷电状态（State of Charge，SOC）估计； 包括参数文件、模型文件两种，模型文件分别仿真了110A恒流、110A脉冲和ECE15工况； 建模采用基于PEGV的电池等效模型对SOC进行估计，并且加入了温度修正等。 模型比较简单，原理清楚，适合对电动汽车动力电池SOC的估计有兴趣的初学者参考学习，学习前请阅读2到3篇基于电池PNGV等效电池模型的动力电池SOC估计方面论文，这样对理解模型更有帮助。(A MATLAB/Simulink model, on the electric vehicle power battery State of Charge, SOC estimates Including the parameter file and the model file, the model file simulates 110A constant current, 110A pulse and ECE15 working condition respectively. The SOC model was used to estimate the SOC and the temperature correction was added. The model is relatively simple, the principle is clear, suitable for beginners interested in electric vehicle power battery SOC estimation, it will be better to read 2 to 3 SOC estimation papers about battery PNGV equivalent battery.)

OFDM —— OFDM(Orthogonal Frequency Division Multiplexing)即正交频分复用技术仿真。(OFDM- OFDM (Orthogonal Frequency Division Multiplexing) that is orthogonal frequency division multiplexing simulation.)

能求出关联矩阵、所有的树，并可选定每一条树，求的的其相应的回路矩阵Qf，及割集矩阵Bf(To find the correlation matrix, all the trees, each tree can be selected, find the circuit of its corresponding matrix Qf, and cut-set matrix Bf)

Driver for receiving and demuxing event-channel signals.