ppm_tb

多元线性回归模型的一般形式 参数估计（ OLS估计） 假设检验 预测 (The general form of the multiple linear regression model parameter estimation (OLS estimates) hypothesis testing prediction)

This file is the programs of (chapter 9) of book (Modeling the Wireless Propagation Channel a Simulation Approach with MATLAB) which is related The Land Mobile Satellite Channel. It helps you to simulate The Land Mobile Satellite Channe.

采用加权网络中节点强度和权重都是幂率分布的模型，双向PCS控制仿真，能量熵的计算，重要参数的提取，基于人工神经网络的常用数字信号调制，应用小区域方差对比，程序简单。( Using weighted model nodes in the network strength and weight are power law distribution, Two-way PCS control simulation, Energy entropy calculation, Extract important parameters, The commonly used digital signal modulation based on artificial neural network, Application of small area variance comparison, simple procedures.)

本文采用的是先对脉搏波进行经验模态分解，产生一组内在的模函数，每一种模态对应一种物理状态，之后使用ＨＴ得出瞬时的频率和振幅，进而得到边际谱(In this paper, is the first of the pulse wave empirical mode decomposition, resulting in a set of intrinsic mode function, each mode corresponds to a physical state, followed by the use of HT derived instantaneous frequency and amplitude, and thus to be marginal spectrum)

一个完整的GNSS接收机Matlab源程序，包括从中频信号的捕获、跟踪、数据同步、解码、导航定位输出(A complete matlab source code for GNSS receiver including intermediate frequency acquisition racking synchronizationdecodingposition and navigation output)

说明：  fft代码,采用蝶形算法,包括C,matlab和verilog代码(fft code, using butterfly algorithm, including C, matlab and Verilog code)

BIHT中的观测矩阵的另一种改进，实验结果证明，效果更明显(another change of BIHT，perfom very good)

matlab describtion of lte phyisical layer

BAN Network in human body

稀疏表示分类算法在ORL人脸库上的实验，参考文章： Wright J, Yang A Y, Ganesh A, et al. Robust face recognition via sparse representation[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2009, 31(2): 210-227. (Sparse representation classification algorithms on ORL face experiments, refer to the article: Wright J, Yang AY, Ganesh A, et al Robust face recognition via sparse representation [J] Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2009, 31 (2):.. 210-227.)