Pulse_propagation_in_negative_index

说明：  ECG心电信号matlab仿真画图，其中包括P波、Q波、QRS波、S波、T波和U波(Matlab simulation of ECG ECG drawing, including the P wave, Q wave, QRS wave, S wave, T wave and U wave)

迭代学习控制：闭环以及开环控制器间切换，具有PI，D型等多型控制器，具有初态学习模块。(Iterative learning control: Closed-loop and open-loop controller to switch between, with PI, D-type and other type of controller with initial state learning modules.)

k-means聚类算法的matlab代码 截图的 想用还是自己手打吧(k-means clustering algorithm matlab code screenshot or their own hands to fight it.)

在本次仿真中，信道加入了高斯白噪声，收端采用了相干解调的解调方法。附详细的WORD文档说明(In this simulation, the channel joined the Gaussian white noise, closed-ended demodulation using coherent demodulation method. WORD document attached to a detailed description)

贝叶斯估计方法的matlab程序,这是一个简单的例子,但很有用(Bayesian estimation methods matlab program, this is a simple example, but very useful)

代码为模拟退火法，利用matlab工具编写。(the code is simulated annealing which written by matlab.)

实现基于PSO的三维图形的极值计算，并显示中间的搜索过程。(Implementation is based on PSO to calculate the extremum of 3 d graphics and display in the middle of the search process.)

Hopfield Neural Network in Matlab

径向基函数插值使用一系列基函数，它们在每个采样点对称且居中。径向基函数是一类特殊的函数，其主要特征是它们的响应与中心点的距离单调地减小（或增加）。中心、距离刻度和精确的形状是模型的参数。(Radial Basis Function interpolation with biharmonic, multiquadric, inverse multiquadric, thin plate spline, and Gaussian basis functions for Matlab/Octave. RBF interpolation uses a series of basis functions that are symmetric and centered at each sampling point. Radial basis functions are a special class of functions with their main feature being that their response decreases (or increases) monotonically with distance from a central point. The center, the distance scale, and the precise shape are parameters of the model.)

这部分是用MATLAB产生随机过程的一系列源代码.含产生高斯分布随机变量,多变量高斯过程样本的产生,高斯--马尔科夫过程的产生等等..分别运行了这些程序.希望对大家有用(This is partly a random process generated by MATLAB source code of the series. Containing random variables have a Gaussian distribution, multivariate Gaussian process for selecting the sample, Gaussian- Markov process and so on .. have to run the procedure separately . everyone would like to be useful)