fft--demo

用于信号处理的fastica算法源码，希望对大家有帮助(For signal processing algorithm FastICA source, in the hope that everyone has to help)

这个是关于无线射频识别室内定位系统的编程框架，如果你想学习室内定位系统的编程，可以参考这个，可能会给你启发(This is about the RFID indoor positioning system, programming framework, if you want to learn programming indoor positioning system, can refer to this, it might give you inspiration)

this the function written in matalb to addned the white gaussian noise removal

说明：  窄带波束形成基本原理及基于matlab的源代码(The basic principles of narrow-band beamforming and the source code based on matlab)

Included in this distribution is matlab code to generate posterior samples for linear Gaussian and binary matrix factorization (noisy-or) Indian Buffet Process models. Three different posterior sampling algorithms are provided: Gibbs, reversible jump Markov chain Monte Carlo (RJMCMC), and sequential importance sampling (SIS). Only the Gibbs and SIS samplers are provided for the linear Gaussian IBP models.

Omni-directional mobile robot controller based on trajectory linearization

压缩感知，进行图像处理，信号处理可以有效减少信息冗余(Compression sensing, image processing and signal processing can effectively reduce information redundancy)

本代码实现了matlab调用VC的动态链接库与cypress的68013芯片通过usb进行数据交换(Matlab code implements the dynamic link library called VC and cypress in the 68013 chip data exchange via usb)

说明：  实现Matlab读取ArcGIS文件，只要设置Matlab路径到文件夹就行(Read ArcGIS achieve Matlab files, simply set the path to the folder Matlab on the line)

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.)