a1

说明：  一些偏最小二乘法（PLS)间隔偏最小二乘(siPLS)联合区间偏最小二乘等的建模代码。(A number of partial least squares (PLS) interval partial least squares (siPLS) Joint interval partial least squares modeling code, etc..)

This letter addresses the problem of fetal electrocardiogram (FECG) extraction. A class of source extraction algorithms is proposed, which uses a combination of two di® erent approaches: Barros s source extraction approach and HyvÄ arinen s ˉxed- point approach.

针对混沌参数调制( C P M) 的电力线通信( P L C) 中谐波引起的窄带干扰， 两阶段动态估计方法根据最小 相空间体积( MP S V) 准则估计模型参数， 计算量大。为此， 提出将未知参数合并到增广状态矩阵的联合卡尔曼滤 波方法， 避免了专门的参数估计过程， 在提高增益性能的同时有效降低了计算量。方法的性能通过对混沌电力 线通信下的单音干扰和多音干扰的有效抑制得到了验证。 (For the chaotic parameter modulation (CPM) of the power line communication (PLC) in the narrow-band interference caused by harmonics, two-phase dynamic estimation methods with minimum phase space volume (MP SV) criterion estimate model parameters, calculation of volume. Toward this end, the unknown parameters into augmented state matrix of the joint Kalman filter, to avoid the special parameter estimation process, while improving the performance gain reduces the amount of calculation. Method of performance under the power line communication by chaotic multitone jamming tone interference and the effective suppression has been verified.)

主要介绍matlab程序下动态数据的采集(Matlab program introduced under the dynamic data collection)

对输入信号峰均比以及信号邻道泄露ACPR的处理(peak digitalsignal handle)

libsvm的最新函数包，包含了各种语言的接口，可方便的实现分类，回归等问题(libsvm package)

matlab7.0 编程基础 电子教程,大家看看有需要的吗(matlab7.0 based electronic programming guide, we need to look at?)

各类实现np问题的matlab算法，本人做4年数学建模累积的，内有蚁群，bintlp，弗洛伊德，kruskal等等程序(Np problem matlab realize all kinds of algorithms, mathematical modeling I did four years of accumulation, there colony, bintlp, Freud, kruskal etc. Program)

A Solution Manual for(Proakis)Digital Signal Processing (Solution)

包含一元线性回归分析、多元线性回归分析、逐步回归分析、非线性回归分析、主成分分析、因子分析、层次聚类分析、判别分析、自相关分析和自回归分析的全套Matlab源代码(MATLAB source code including linear regression analysis, multiple linear regression analysis, stepwise regression analysis, non-linear regression analysis, principal component analysis, factor analysis, hierarchical clustering analysis, discriminant analysis, autocorrelation analysis and autoregressive analysis)