psotb-beta-0.3

说明：  高质量的OFDM仿真代码，有误码率仿真图。非常好用。(OFDM simulation of high-quality code, bit error rate simulation map. Very easy to use.)

By building a nonlinear function relationship between an d the error signal，this paper presents a no— vel variable step size LMS(Least Mean Square)adaptive filtering algorithm．(By building a nonlinear function relationship between an d the error signal, this paper presents a no-vel variable step size LMS (Least Mean Square) adaptive filtering algorithm.)

基于matlab的DTMF数字拨号音合成，通过的简单的时域连接，用于进一步分析合成效果。DTMF2是分析部分，用于显示时域波形，频谱图和语谱图。(Based on the synthesis matlab DTMF digit dialing tone, and connected by a simple time domain, for further analysis synthesis results. DTMF2 the analysis section, time-domain waveform, spectrum and spectrogram displays the)

关于中性点接地故障分析仿真，仿真了中性点接地系统零序电流大小及规律。(On neutral ground fault analysis and simulation, simulation of neutral grounding system zero sequence current size and regularity.)

利用人工势场法进行移动机器人的路径规划的matlab程序。包含具体的讲解。(The use of artificial potential field method for mobile robot path planning matlab procedures. Contains specific explanation.)

Blind Source Seperation (BSS) now is a important technology. Independent Component Analysis (ICA) is the main technique of BSS. Suppose we mix many non-Gausse signal sources,ICA can seperate the mixed signal to orignal signals without any information. This Matlab Code simulate the using ICA for Multi User Detection (MUD) in CDMA system. We demo the CDMA system with 30 Users, and use ICA seperate the signal of each user at Base Transmit Station (BTS) with the only 30 Users signal.

包含优化类的几个简单示例程序，matlab程序运行时导入数据文件作为输入参数，多姿态，多角度，有不同光照,研究生时的现代信号处理的作业，计算多重分形非趋势波动分析。( Optimization class contains several simple sample programs, Import data files as input parameters matlab program is running, Much posture, multi-angle, have different light, Modern signal processing jobs when the graduate, Calculate the multifractal trend fluctuation analysis.)

自己编写的基本的二进制GA程序，均匀交叉，单点变异(It is the cold of simple binary GA)

支持向量机和BP神经网络虽然都可以用来做非线性回归，但它们所基于的理论基础不同，回归的机理也不相同。支持向量机基于结构风险最小化理论，普遍认为其泛化能力要比神经网络的强。为了验证这种观点，本文编写了支持向量机非线性回归的通用Matlab程序和基于神经网络工具箱的BP神经网络仿真模块，仿真结果证实，支持向量机做非线性回归不仅泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。 (Support Vector Machine and BP neural network, even though there can be used to make non-linear regression, but they are based on the theoretical basis for the different, the mechanism of regression is not the same. Support vector machine based on structural risk minimization theory, generally considered the generalization ability of neural networks than the strong. To test this view, the paper prepared by non-linear regression support vector machine procedures and based on a common Matlab neural network toolbox of BP neural network )

电磁学代码，matlab编写绝对自己创作的(Electromagnetics code, matlab absolutely prepared their own creation)