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simulation and software radio for mobile communications 书中有详细的移动通信方面的matlab程序，对通信仿真有指导作用(simulation and software radio for mobile communications book detailed matlab mobile communications procedures, guidance on the role of communication simulation)

说明：  Nakagami-m分布能用来对比瑞利分布条件更苛刻的衰落信道进行建模，最适合于郊区无线多径信道上接受的数据信号，瑞利分布是它 时的特例。(Nakagami-m distribution can be used to model fading channels with more stringent Rayleigh distribution conditions. It is most suitable for data signals received on suburban wireless multipath channels. Rayleigh distribution is its special case.)

main executing reference usage: executeMain.m -------------------------------------------------------------------------------- The geometrical interpretation of the 1-D DFT may have been seldom seen or introduced. The utility demonstrates the visualization of the phenomenon. * Caveat: - Help section yet to be included. - For educational reference only. You may also wish to visit Professor Grigoryan s weblink at: http://bit.ly/ProfessorArtyomGrigoryan

说明：  基于MATLAB的OFDM系统仿真分析 pdf格式，不错(MATLAB-based simulation analysis of the OFDM system pdf format, good)

windows环境下的截包代码，学习用，很有价值(windows environment cut package code, learn to use, great value)

用分步傅里叶变化法求解非线性薛定谔方程，适用于非线性光纤系统(split_step_fourier method for nonlinear fiber optic)

在ｍａｔｌａｂ上实现的特定人小词汇量的语音识别程序。先输入１０个模板，第１０个为退出命令，然后再根据提示进行识别(in Matlab achieve specific small- vocabulary voice recognition procedures. Importing 10 templates, 10 to withdraw from the order, then under the prompt identification)

在信号分析中，我们常把信号进行矢量分解，也就是将信号分解为频率相同、峰值幅度相同但相位相差90的两个分量。该程序实现将信号分解为I路和Q路。(In signal analysis , we often decompose the signal vector , that is, the signal is decomposed into the same frequency , the peak amplitude of phase 90 of the same, but the two components . The program implementation will signal into I and Q branches .)

《电力电子应用技术的MAtlab仿真》一书影印版。(Power electronics simulation base on MAtlab)

有用的文件 matlab程序 对于初学者很有帮助 尤其是广义简约梯度法(Especially useful file matlab program for beginners helpful Generalized Reduced Gradient Method)