waveletdenoisingmatlabprogrem1

frequency domain filters

用matlab语言实现无线传感器网络LEACH算法，和其改进算法。并比较改进算法的优点。(Matlab language implementation wireless sensor network LEACH algorithm, and the improved algorithm and compare the advantages of the improved algorithm)

利用已识别出的参数，得到Bouc-Wen模型的力-位移曲线。(Obtain the force-displacement curve of Bouc-Wen model, using the identified parameters.)

本程序是对V-BLAST系统及其检测算法的仿真，可采用BPSK,QPSK,16QAM,64QAM调制。检测算法为ML，MMSE,ZF,以及采用迫零的连续干扰消除检测算法。(This procedure is the V-BLAST system and its detection algorithm simulation, can be used BPSK, QPSK, 16QAM, 64QAM modulation. Detection Algorithm for the ML, MMSE, ZF, and the use of zero-forcing successive interference cancellation algorithm.)

用Kalman滤波方法估计目标航迹的Matlab源程序(this study is Kalman Filter algorithm of a very good process)

一个载波恢复与符号定时的仿真。 载波恢复使用平方环，符号定时基于早迟门，发送信号采用BPSK调制方式，统计计算的误码率。(A carrier recovery and symbol timing simulation. Carrier recovery loop using the square, the symbol timing based on early-late gate, sending a signal using BPSK modulation, bit error rate statistics calculations.)

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 )

基于FFT变换、DCT变换、HT变换、小波变换和矢量量化技术的图像压缩的Matlab实现。(Based on the FFT transform, DCT transform, HT transform, wavelet transform and vector quantization image compression technology, the Matlab implementation.)

图形反演，这个函数有几个有用的功能，在医学图形处理的领域。(InvertIm generalized image inversion (grayscale reversal) This function has several options that are useful for inversion of medical images for use in other software. )

kfdemo.m is a Matlab script file to run a demonstration of the Bayesian Kalman filter. It loads file kfdemo.mat (saved as version 4 so that it will read in either v4 or v5 Matlab). The other files are called by kf.m (the Kalman filter) or included as they may be useful. Normalis.m normalises data to zero-mean, unit variance along components. I always do this before any further analysis.(kfdemo.m Matlab is a script file to run a dem onstration of the Bayesian Kalman filter. It lo kfdemo.mat ads file (saved as version 4 so that i t will read in either v4 or v5 Matla#$#!254253#!#$C-Algorithm- XSL.zip!#$#"C algorithms suite" of source code, Shi-Liang Xu book, a lot of highly efficient C language algorithms, those self-help programming.)