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阵列信号处理中的其中一个传统子空间方法仿真程序，二维music算法。(One of the traditional subspace method simulation program in array signal processing, the two-dimensional music algorithm.)

matlab c++ 联合编程简单示例，具体过程可以参照我的blog：http://blog.csdn.net/owldestiny/archive/2009/03/07/3966340.aspx(matlab c++ United programming easy example, the specific process can refer to my blog: http://blog.csdn.net/owldestiny/archive/2009/03/07/3966340.aspx)

说明：  运用VC编写的如何在VC中调用MATLAB(use in the preparation of the VC Calling MATLAB)

此matlab函数可以在ECEF和ECI坐标之中转转换地点和速率信息。 ，经测试可直接使用。 (This Matlab function can be transferred into the ECEF and ECI coordinate conversion location and rate information. Has been tested and can be used directly.)

利用vc和matlab混编，调试mex文件的方法。附带VC详细操作步骤以及C++源程序(use VC and matlab to debug code )

智能天线技术是第三代移动通信系统的关键技术之一，也是国内外热门的研究课题。由于无线移动通信的信道传输环境具有复杂性和不确定性，存在多径衰落和时延扩展，因此造成了符号间串扰、同信道干扰、多址干扰等，这些干扰降低了链路性能和系统容量，智能天线技术是解决以上问题的方法之一。 本文首先阐述了智能天线和白适应波束形成的基本理论，然后对自适应算法进行了研究。对一些基本的自适应算法最小均方算法、恒模算法及递推最小均方算法进行了分析讨论，用计算机仿真的结果论证了算法的性能。针对相干干扰介绍了空间平滑技术，对传统的相干干扰抑制方法-空间平滑法进行了分析，采用改进算法有效降低了空间平滑算法的运算量。对信号波达方向(DOA)的估计是智能天线研究的另一关键问题。第四章在介绍了阵列信号处理方法的基础上，先简单介绍了Bartlett、Capon、MUSIC等空间谱估计算法，分析了信源数目过估计与欠估计情况下的MUSIC算法性能，提出一种改进算法，在信源数目有误差的情况下该算法的性能良好。第五章针对多径干扰环境，在分析MMUSIC算法的基础上，本文提出了基于低秩矩阵逼近法的改进MUSIC算法(In this paper, firstly, the author illustrates the principles of smart antenna and adaptive beam forming, and then introduces some typical adaptive algorithms, the LMS ,CMA and RLS algorithms are analyzed and discussed and simulate them in the computer to prove their capability. but they have the disadvantage of high complexity, so they are not fit for practice. The paper analyses the conventional method rejecting spatial smoothing coherent interfering signals, which is spatial smoothing technique)

Matlab编写的弹道分析算法-MATLAB源代码(Trajectory analysis algorithms written in Matlab-MATLAB source code)

matlab 分类程序 金融工程 股票 (matlab matla)

This article demonstrates how to use the WindowsVistaRenderer and how it was created. Background

This a self-contained package including the 2-D DWT and inverse DWT routines. The included matlab routines are used to generate noisy example images and disply the result of denoising.