新建文件夹

：提出一种基于独立成分分析（ICA）和位隙动态分组技术的超高频（UHF）射频识别（RFID）多标签防碰撞算法。利用ICA 算法实现多目标的同时识别，利用动态位隙标签分组保证阅读器同时读取的标签数少于或等 于其天线数，从而使ICA 工作于非欠定状态(A novel ultra high frequency (UHF) radio frequency identification（RFID）anti-collision algorithm based on independent components analysis (ICA) and dynamic bit-slot grouping technology was proposed. The ICA algorithm was used for identifying several tags simultaneously. The dynamic bit-slot tags grouping technology was used for ensuring the number of tags read by a reader at the same time was less than or equal to its antennas’ number, and enabling the ICA wouldn’t work in an underdetermined state. Theoretical analysis and simulated experimental results show that the tags identification rate of the proposed algorithm is far more than that of traditional stochastic or deterministic TDMA RFID anti-collision algorithms.)

Script file to draw i-v curves of pv module

信号相加,卷积的应用，从别的地方学习的，貌似有点问题，大家可以参考一下(From other place)

计算声压级平均值的四种方法：算术平均法，声压均方根平均法，能量平均法等(Four methods to calculate the average of sound pressure level are arithmetic average method, pressure square root mean method, energy averaging method and so on)

使用matlab打开扩展名为vff文件的程序(Matlab extension used to open documents vff)

In this i attached matlab code for indoor localization using WIFI and FM signal features classified by KNN classifier to predict the fingure print of the building structure.

show the results of using AF in cooperative communications

相关向量机(RVM)的matlab源程序，包含快速算法，内含代码使用说明。 RVM采取是与支持向量机相同的函数形式稀疏概率模型，对未知函数进行预测或分类。 优点： (1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布. (2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间. (3) RVM不需要估计过多的参数. (4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好(Relevance Vector Machine (RVM) of the matlab source code, including fast algorithm that contains code for use. RVM support vector machine is taken the same functional form sparse probabilistic model to predict the unknown function or classification. Advantages: (1) is not only the amount of output predicted target point estimates, but also the distribution of predicted values ​ ​ can be output. (2) using a smaller number of support vectors, thereby significantly reducing the output target amount predicted value calculation time. (3) RVM does not require excessive parameter estimation. (4) RVM meets Mercer theorem on the kernel function is not limited, and better adaptability)

基于微分器的PID控制matlab程序源码(PID control based differentiator)

isodata聚类算法用于聚类类IRIS数据，分类效果较好，运行稳定(isodata clustering algorithm for clustering classes IRIS data classification better, stable operation)