Rayleigh-Fading

我这是论文中用到人工鱼群算法，为matlab代码。希望对对大家有用。(This artificial fish-swarm algorithm code in matlab was used in my paper,I hope it is usefull for you.)

XOR问题是神经网络里面一个经典的问题，本例子使用Matlab自编SVM对XOR问题进行解决~(XOR problem is a classical neural network inside the issue, the examples of the use of Matlab for self-SVM to solve the XOR problem ~)

很好用的matlab蚁群算法，已经调试过可以使用(Good use of Matlab ant colony algorithm, debugging can use)

this is one of the best satelite code in the world to find the look angle

完整的OFDM链路程序并作了较为具体的解析从基本的bpsk,qpsk,qam到实际的ofdm系统，cdma链路，mac层仿真分析.(Orthogonal frequency division multiplexing (OFDM) is becoming the chosen modulation technique for wireless communications. OFDM can provide large data rates with sufficient robustness to radio channel impairments. Many research centers in the world have specialized teams working in the optimization of OFDM for countless applications. Here, at the Georgia Institute of Technology, one of such teams is in Dr. M. A. Ingram’s Smart Antenna Research Laboratory (SARL), a part of the Georgia Center for Advanced Telecommunications Technology (GCATT). The purpose of this report is to provide Matlab code to simulate the basic processing involved in the generation and reception of an OFDM signal in a physical channel and to provide a description of each of the steps involved. For this purpose, we shall use, as an example, one of the proposed OFDM signals of the Digital Video Broadcasting (DVB) standard for the European terrestrial digital television (DTV) service.)

多种曲线拟合牙齿轮廓,有最小二乘法，beizer曲线，Newton插值，拉格朗日插值法……(interpolation to contour teeth)

abaqus中的动态分析方法,含有inp、for文件希望能给动态分析，提供点参考(Methods of dynamic analysis of abaqus, containing the inp, hope can give a dynamic analysis for file, provide a point of reference)

卫星FDM例子的MATLAB代码,运行结果为BER和信号星座图(Satellite FDM examples, MATLAB code)

autocov computes the autocovariance between two column vectors X and Y with same length N using the Fast Fourier Transform algorithm from 0 to N-2. The resulting autocovariance column vector acv is given by the formula: acv(p,1) = 1/(N-p) * sum_{i=1}^{N}(X_{i} - X_bar) * (Y_{i+p} - Y_bar) where X_bar and Y_bar are the mean estimates: X_bar = 1/N * sum_{i=1}^{N} X_{i} Y_bar = 1/N * sum_{i=1}^{N} Y_{i} It satisfies the following identities: 1. variance consistency: if acv = autocov(X,X), then acv(1,1) = var(X) 2. covariance consistence: if acv = autocov(X,Y), then acv(1,1) = cov(X,Y)

This ClassVisitor removes InnerClasses and EnclosingMethod attributes in classes that are retargeted or that refer to classes that are retargeted.