BER-for-BPSK

FFT的matlab实现,利用蝶形算法计算fft的matlab(Matlab implementation of FFT, using the matlab fft butterfly algorithm)

基于隐马尔可夫模型的学习推理的具体示例教程。(Learning reasoning based on hidden markov model concrete examples of tutorial )

详细介绍了在概率统计学中应用matlab,并且为初学者提供实力(Introduces in detail the application of probability statistics in MATLAB, and for beginners to provide strength )

IEEE 802.11a系统OFDM仿真。假设OFDM系统物理层采用802.11a系统物理层参数，其中，1个长训练符号与6个OFDM数据符号构成1帧，信道为单径瑞丽衰落信道，接收端采用理想信道估计和利用训练符号进行信道估计时的误比特性能(IEEE 802.11a system OFDM simulation Assuming that the OFDM system physical layer uses the 802.11a physical layer parameters, among them, 1 long training symbols and 6 OFDM data symbol consisted of 1 frames, the channel into a single path Ruili fading channel, the receiver uses the ideal channel estimation and utilizes the training symbols to estimate channel bit error performance of the)

fault detection and classification

基于人工神经网络的常用数字信号调制，采用波束成形技术的BER计算，采用偏最小二乘法，相控阵天线的方向图（切比雪夫加权），使用matlab实现智能预测控制算法，本科毕设要求参见标准测试模型。( The commonly used digital signal modulation based on artificial neural network, By applying the beam forming technology of BER Partial least squares method, Phased array antenna pattern (Chebyshev weights), Use matlab intelligent predictive control algorithm, Undergraduate complete set requirements refer to the standard test models.)

该代码为利用几何不变矩提取图像几何特征的代码，用matlab编写，提取7个Hu矩为特征向量。可以用于基于内容的图像检索(The code for the image using the geometric moment invariant geometric features extracted code, written with matlab to extract seven Hu moments as features. Can be used for content-based image retrieval)

MATLAB QPSK_RAYLEIGH

This folder contains Matlab functions for the Enhanced Interval Approach (EIA) in: Simon Coupland, J. M. Mendel and Dongrui Wu, “Enhanced Interval Approach for Encoding Words into Interval Type-2 Fuzzy Sets and Convergence of the Word FOUs,” IEEE World Congress on Computational Intelligence, Barcelona, Spain, July 2010. All following functions were tested in Matlab 7.4.0 (R2007a) under Windows 7: centroidIT2: Compute the centroid of an IT2 FS. EKM: Implement the Enhanced KM algorithms. IA: Implement the Interval Approach for word encoding. mainJPL: Illustrate IA and EIA using the JPL dataset. mainWeb: Illustrate IA and EIA using the Web dataset. mg: Compute the membership grades of a vector of numbers on a T1 FS. plotFigures: Plot Figs. 3.18, 3.19 and 3.20 in the book. plotIT2: Plot an IT2 FS. Last modified by Dongrui Wu (dongruiw@usc.edu), May 2, 2010.

kalman递归理论的详细讲解,通谷易懂,想弄明白kalman理论的同志一看便知!(a easy understanding for Kalman theory.it is very useful for new leaner! )