Quadrupole

主要就是实现L_M优化算法，用matlab写的 转成c该很容易的，用来仿真用的，希望大家给出点意见，第一次上传(err)

Auto-correlation and cross-correlation - graphic version(Auto-correlation and cross-correlation- graphic version)

研究脑电的经典文章，国外大牛写的，值得推荐，研究脑电信号处理的方法(EEG studies classic article, written by Daniel abroad, it is recommended to study the EEG signal processing methods)

用matlab做方差分析的几个例程包括：单因素一元方差分析，双因素一元方差分析 非参数方差分析(ANOVA using matlab to do a few routines include: single-factor analysis of variance one yuan, two-factor analysis of variance one yuan non-parametric analysis of variance)

从数学角度分析鲁棒和非线性控制，电子书，欢迎下载。(Mathematical Methods for Robust and Nonlinear Control)

遥感图像融合及效果评价 brovey融合、IHS、PCA、WT融合及使用各种指标进行评价。(Remote sensing image fusion and uation on brovey fusion, IHS, PCA, WT integration and use of indicators for uation.)

说明：  internal on line partial discharge

CVI_MATLAB混合编程方法,多少还是有点用,大家随便看看吧(CVI_MATLAB hybrid programming approach, the number is still somewhat used, everyone just take a look at it)

Create a channel object that describes the channel that you want to use. A channel object is a type of MATLAB variable that contains information about the channel, such as the maximum Doppler shift.

用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。(Use Parzen Windows method or the kn neighbor method estimated probability density function, draw the bayes classifier, to test sample to test, and the parameter estimation is based on the classifier and get the difference of classification performance. 2. At the same time the height and weight data as the characteristic, with Fisher identification method for linear classifier, and the application of the classifier to training and test sample, investigation and test training error condition. Will the training sample and utility of decision on the drawing boundary paint, and at the same time before the Bayes method with optimal classifier also paint chart, the result of the comparison of the similarities and differences. 3. Select the above or before any a kind of method of experiment, with a method for training set in the estimation error rates, and on the test set get error rates are compared.)