paifei_v35

基于羽田孜模型的预知的路径损耗 基于爱德华兹和德金模型的路径损失预知 基于帕森斯与伊布拉因模型的路径损耗预知(Tsutomu Hata model based on predictable path loss payments based on Edwards and the German model to predict the path loss model based on Parsons and Ibraim predict the path loss)

物理光学方法 近似计算散射体RCS POFACETS is an implementation of the physical optics approximation for predicting the radar cross section (RCS) of complex objects. It utilizes the scientific computational features of MATLAB and its Graphical User Interface (GUI) functions to provide an error-free encoding of input parameters and efficient calculation of RCS. POFACETS provides a convenient tool for a “first cut” at the RCS of complex shapes by representing its constituent parts by triangular facets. The software calculates the monostatic or bistatic RCS of the object for the parameters specified(POFACETS is an implementation of the physical optics approximation for predicting the radar cross section (RCS) of complex objects. It utilizes the scientific computational features of MATLAB and its Graphical User Interface (GUI) functions to provide an error-free encoding of input parameters and efficient calculation of RCS. POFACETS provides a convenient tool for a “first cut” at the RCS of complex shapes by representing its constituent parts by triangular facets. The software calculates the monostatic or bistatic RCS of the object for the parameters specified)

说明：  基于matlab的数字水印源程序，并附详细论文(Matlab source based on digital watermarking, together with details of papers)

Compute various Allan deviations for a constant-rate time series

OpenTSTOOL_win，时间序列工具箱。里面包含用来编程的两个时间序列，让大家更加容易学习。(OpenTSTOOL_win, time series toolbox. Which contains two time series used to programming, easier to learn.)

网上找的关于LDPC码的几篇硕士论文。包括几种改进的算法。(Online on the LDPC code to find a few master' s thesis. Several improvements, including algorithms.)

speaker recognization using wav files

实现定时控制，非常实用，可以直接调用，有需要的可以下载(Achieve timing control, very practical, you can directly call the need to be downloaded)

说明：  在同一张图上仿真多幅度电平M电平PAM在M=2,4,8,16时的符号差错概率。(In the same graph simulation multi-level rate of M-level PAM at M = 2,4,8,16 when the symbol error probability.)

Matlab入门资料，关于Matlab的一些基本运用。(rumenziliao)