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说明：  本程序实现LPP降维功能，用于多模态故障诊断中(This procedure realize the LPP dimension reduction function, used in multimodal fault diagnosis )

粒子群算法是求解函数优化问题的一种新的进化算法，然而它在求解高维函数时容易陷入局部最优，为了克服这个缺点，提出了一种新的粒子群算法，算法对粒子的速度和位置更新公式进行了改进，使粒子在其最有位置的基础上进行位置更新，增强了算法的寻优(PSO for solving function optimization problems is a new evolutionary algorithm, but it is easy to solve high-dimensional function into local optimum, in order to overcome this shortcoming, a new particle swarm algorithm, algorithm on the particle velocity and location of the update formula has been improved, so that particles in the most positions on the basis of location updates, enhancements, optimization algorithm)

卡尔曼滤波FUN函数，需要的自己下载。很好很强大的(The Kalman filtering FUN function, need to download. Very very strong)

多用户MIMO系统中一种基于干扰抑制类的预编码方法——最大信漏噪比预编码（SLNR）(an interference suppression algorithm for multi-user MIMO system-SLNR precoding)

matlab统计基因序列多序列比对中各个多态性位点中碱基个数(matlab statistics sequence for multiple sequence alignment of various polymorphisms in the number of base)

Implementation of the paper "Teeth Segmentation in Digitized Dental X-Ray Films" along with the paper itself

用MATLAB来仿真FSK、PSK、DPSK的调制、解调过程，并通过实验来比较它们的误码率和信噪比的关系。内附有matlab源代码(Using MATLAB to simulate FSK, PSK, DPSK modulation, the demodulation process, and to compare their bit error rate and signal to noise ratio by the empirical relationship. Enclosed is the matlab source code)

am fine and i feel to in joy that

jmag和matlab与psim联合仿真的教程，内容非常详细，英文版的，国内资料非常少。(Jmag and MATLAB and PSIM co simulation tutorial, the content is very detailed, the English version of the domestic information is very small. )

一共包含了5个ICA的算法，其中： fastica.m文件中的ICA算法是基于负熵的； m_fastica.m文件中的ICA算法是基于负熵的改进算法； fastica_kurt.m文件中的ICA算法是基于峭度的； fastica_ML.m文件中的ICA算法是基于互信息的； NLPCA.m文件中的ICA算法是基于非线性PCA的。(Contains a total of five ICA algorithm, in which: fastica.m file in the ICA algorithm is based on negative entropy m_fastica.m file in the ICA algorithm is based on negative entropy of the improved algorithm fastica_kurt.m file in the ICA algorithm is Based on Kurtosis fastica_ML.m file in the ICA algorithm is based on mutual information NLPCA.m file in the ICA algorithm is based on nonlinear PCA' s.)