Modern_Signal_Processing

本文档详细介绍了物理内存的基本内容，并且讲述了内存静态分区和动态分区方法(This document details the basic elements of physical memory, and memory about the static and dynamic partition method of Division)

本论文利用TI公司的16位定点DSP芯片TMS320VC5416-160的硬件、软件结构和特性实现了数字滤波器的设计。深入研究了DSP芯片的硬件开发技术和软件编程技术及调试技巧 在MATLAB环境下,利用MATLAB语言编写程序对IIR滤波器进行仿真并得到滤波器的系数 关于matlab与DSP等。(In this paper, the use of TI' s 16-bit fixed-point DSP chip TMS320VC5416-160 hardware, software structure and characteristics of a digital filter design. In-depth study of the DSP chip technology hardware and software programming and debugging skills in the MATLAB environment, using MATLAB programming language for simulation of the IIR filter and the filter coefficient matlab and DSP and so on.)

能够修改交织深度，来实现任意长度的交织，采用802.11a的方案，实现分组交织(Interleaving depth can be modified to achieve any length intertwined, using 802.11a solution, implementing the packet interleaving)

vbalst 的自己编写的迫零检测程序，包含有误差和无误差两种情形(vbalst' s own testing procedures prepared by zero-forcing, contains two kinds of errors and error-free case)

基于matlab图像界面，图像配准的源程序，可以运行，非常好用。(Matlab image based interface, the source image registration, you can run, very easy to use.)

simulation of performance of equalizer mmse and zf with technology MIMO

Distributed fault identification via non-parametric belief propagation

A highly comprehensive lecture in understanding basics of electronics

说明：  dea in matlab for windows

这个zip文件中包含的原则和双方的扩展卡尔曼滤波（EKF）和全球定位系统（GPS）算法简要说明。它的主要目的是提供一个相对容易实现的扩展卡尔曼滤波，在我们使用的输入函数的形式，而不是禁止函数处理符号表达式。它也可作为一个简要介绍了卡尔曼滤波算法GPS和学习它的意思。在为EKF的例子，我们提供的原始资料，同时使用的定位扩展卡尔曼滤波和最小二乘法的任务和解决方案。 有四个M文件和两个数据文件。 Extended_KF.m包含EKF的函数体。另一些功能和GPS的示例数据文件。(This zip file contains a brief illustration of principles and algorithms of both the Extended Kalman Filtering (EKF) and the Global Position System (GPS). It is designed primarily to provide a relatively easy-to-implement EKF, in which we use symbol expressions as the form of input functions rather than the forbidding function handles. It also serves as a brief introduction to the Kalman Filtering algorithms for GPS and a mean of learning it. In the example for the EKF, we provide the raw data and solution for the positioning task using both EKF and the Least Square method. There are four m files and two data files. Extended_KF.m contains the function body of the EKF. Others are functions and data files for the GPS example.)