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eeg数据处理,此代码为美国ucsd脑科学实验室开发的著名实验程序。(eeg data processing)

一个汽车的fuzzy的控制,能很好地应用FUZZY的特点(a car fuzzy control can be well applied to the characteristics FUZZY)

当前经典的合成孔径雷达成像算法为：RD，CS和RMA。压缩包里有这三个算法的Matlab代码，这些代码对初学者是非常有用的。 (Three classic image formation algorithm for Synthetic Aperture Radar(SAR) are RD, CS, RMA. They can be obtain in Matlab Code, and they may be usefull to beginners. )

(1)针对在线计算量大这一缺陷，将预测控制中的柔化输出信号的思想推广到柔化输入信号，使得约束条件被简化为仅对当前控制量的约束，可以直接计算得出；同时该方法避免了求逆矩阵，大大减小了计算量，并能够保证控制算法的可行性和良好的控制性能。 (2)针对传统算法中设计参数整定困难这一缺点，应用基于BP神经网络变参数设计的广义预测控制算法，实现了对控制量柔化参数的在线调整。 (3)利用带有遗忘因子的最小二乘法对系统辨识。本文通过仿真发现该方法对于Hénon混沌系统并不完全适用，可考虑利用其他优化系统辨识的方法对本方法进行改进，以期达到更好的辨识效果。 (4)针对系统稳定性分析复杂，本文在控制增量前加入前馈因子，保证所选的Lyapunov函数使闭环系统满足Lyapunov稳定判据，由此证明闭环系统稳定。 (1. To solve the problem of GPC huge computation, algorithm with input increment constraints is presented in which the concept of output softness was used to soften the input increments．As a result, the constraints are simplified to be the only one constraint on the current control increment which can be computed directly. At the same time, it needn’t computing the inverse matrix and thus reduces large computation. Moreover, it guarantees the feasibility of the algorithm and has good control performance． 2. To overcome the difficulty in the choice of tuning parameters in traditional GPC, a GPC algorithm with variable parameter design based on BP neural network. is presented，in which the input softness parameters are tuned on line. 3. In this paper, we Identify system by using the least square method with forgetting factor. However, after system simulation, we realize that this method doesn’t fit the Hénon chaotic system perfectly. So we recommend modify this method by other Optimizati)

matlab 关于主成分分析的详细代码，附带数据及gui界面文件，可直接运行(matlab on principal component analysis of the detailed code , files with data and gui interface can be run directly )

information about analog com for ir sensor interface

matlab guide 界面编程 带登陆界面 等 用于学习(Matlab guide interface programming, landing interface, etc., for learning.)

MATLAB R2008图形与动画实例教程源程序(MATLAB R2008 graphics and animation tutorial source code examples)

matlab做的图像检索源码，算法实现不错，很有借鉴作用，对初学者更是适用。(matlab source code to do image retrieval algorithm to achieve good, very useful reference for beginners it is applicable.)

说明：  CA算法可以将数量型属性划分成若干个优化的区间，它综合了分层聚类于划分聚类的优点，对于给定的不同的初始类个数，CA算法能随着迭代过程的不断进展改变类的数目，一些竞争力差的类即类的基数小于给定阙值的类将在迭代过程中不断消失，最终得到能够有效体现数据实际分布情况的优化聚类个数。(CA algorithm for quantitative attributes can be divided into a number of the interval optimization, hierarchical clustering which combines the advantages of clustering in the division, for a given number of different types of initial, CA algorithm as the iterative process the continuous progress of change in the number of categories, some categories of poor competitiveness of the base type that is less than the value of a given category Que iterative process will continue to disappear and eventually be able to effectively reflect the actual distribution of data to optimize the number of clustering.)