gatbx

说明：  很不错的一本英文书籍，全面详细的讲解了simulink，从基础到进阶到高级应用。(Simulation and Model-Based Design 1.What Is Simulink? 2.Building a Model 3.How Simulink Works 4.Simulink Basics.......)

说明：  由matlab开发的hybrid系统的描述语言，用于系统的建模、仿真、最优控制等。(from Matlab development of the hybrid system description language for the modeling, simulation, Optimal control.)

一个颜色空间转换的程序，可以实现任何空间的转换，如rgb到L*a*b颜色空间转换等。(A color space conversion process, conversion of any space can be achieved, such as rgb to the L* a* b color space conversion.)

以时滞切换系统为对象，给出了使系统稳定的输出状态反馈器设计条件(Dynamic output feedback control for a class of switched delay)

模拟噪声的程序，可以根据需要改写，主要功能是实现噪声模型 (Additive Noise Channel/Additive Guassian Noise Channel is the simplest of all channels. File usage details: op_channel = additivenoise(input_signal) mathematical Model: s(t) input signal to channel (=sig_ip) n(t)additive random noise process added by channel (=noise_mat) a(t) attenutation factor , here it is taken as random(=att_fact) out put signal r(t) = a .* s(t)+ n(t) an additional file named through_anc is there which shows 2 figures, 1. input signal 2. output signal )

还是MATLAB的例程，绝对实用。请接纳。谢谢！(Or the MATLAB routine, absolutely practical. Please accept. Thank you!)

matlab有限元工具箱的应用例子，找了好久才找到的，望对大家有用(Application of finite element toolbox matlab example, to find a long time to find, and hope it would be useful)

leach协议的MATLAB实现，主要体现leach的算法过程。(leach algorithm based on MATLAB。)

实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))

说明：  用数字滤波器进行脑电信号处理，可以滤除脑电信号中的无用成分，达到对脑电信号去噪的效果。(Brain with digital signal processing filter can filter out unwanted components in the EEG, to the effect on EEG denoising.)