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Muestreo de se帽ales en matlab

It is the matlab code for denoising an EEG signal using adaptive algorithm. Moreover, the code also explains the performance difference between IIR and FIR comapared to adaptive techniques

说明：  通信信号相干调制解调源码 Fc=10 ％载频 Fs=40 ％系统采样频率 Fd=1 ％码速率 N=Fs/Fd df=10 numSymb=25 ％进行仿真的信息代码个数 M=2 ％进制数(Coherent modulation and demodulation of communication signal source Fc = 10 carrier frequency Fs = 40 systematic sampling frequency Fd = 1 code rate N = Fs/Fd df = 10 numSymb = 25 of the information code to simulate the number of M = 2 hexadecimal number)

译码协同通信的蒙特卡洛仿真 基于最大比合并接收方法(Decoding the Monte Carlo simulation of cooperative communication)

一个duffing模型，一个噪声模型，一篇duffing检测原理，。可检测不同频率的待测信号(a duffing model, a noise model, a duffing detection principle)

纳税风险评估方案及对策,2013西安交通大学数学建模模拟赛matlab代码(Tax risk assessment program and Countermeasures.)

一个帮助外汇交易者判断交易方向的信号，思路是进行突破交易，结合布林带通道和KD指标，KD上涨过程中过滤做空信号，KD下跌过程中，过滤做多信号。(A signal to help foreign exchange traders to judge the transaction direction, train of thought is a breakthrough deal with Bollinger channel and KD index, filter the short signal KD increases, KD falls in the process, filtering the signal to do more.)

P & Q control of DFIG

统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines( This section should give the reader a quick overview of the methods implemented in STPRtool. • Analysis of linear discriminant function: Perceptron algorithm and multiclass modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection of known algorithms solving the Generalized Anderson’s Task. • Feature extraction: Linear Discriminant Analysis. Principal Component Analysis (PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis. • Probability distribution estimation and clustering: Gaussian Mixture Models. Expectation-Maximization algorithm. Minimax probability estimation. K-means clustering. • Support Vector and other Kernel Machines: Sequential Minimal Optimizer (SMO). Matlab Optimization toolbox based algorithms. Interface to the SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers. Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell- Demyanov-Molozenov algorithm )

MATLAB常用函数大全都在这了，很实用(MATLAB functions used in this Daquan, and very practical)