MATLBlayout

移动无线信道COS207模型MATLAB程序(Mobile radio channel model MATLAB procedures COS207)

此资料为《精通matlab金融计算》一书中的光盘程序程序(This information is " proficient matlab financial calculations," a book of the CD-ROM program program)

高斯积分计算程序，用于计算高斯积分点和权系数。(Gauss numerical integral programme)

addition of white gaussian noise

qpsk transmiter with qpska modulator QPSK is a method for transmitting digital information across an analog channel.Data bits are grouped into pairs, and each pair is represented by a particular waveform, called a symbol, to be sent across the channel after modulating the carrier.

代码是根据文献思想自己编写，已经过多次试验，实现对图像处理过程中的svd分解，过程中需要调用一个omp函数，可以自己随便调用一个(The code literature thinking of their own writing, has been repeatedly test svd decomposition of image processing, the process need to call a omp function can casually call a)

地震动非线性时程分析程序，采用matlab程序编程，计算砌体结构在地震作用下结构的反应。(Earthquake nonlinear time history analysis procedures, using matlab programming, computing masonry structure response of the structure under earthquake.)

MATLAB图像处理工具箱。有图像重建，图像压缩，图像恢复等代码。很有用(MATLAB Image Processing Toolbox. Are image reconstruction, image compression, image restoration code. Useful)

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数(Conjugate Gradient method (Conjugate Gradient) is between the steepest descent method between Newton method and a method, it only USES a derivative information, but overcome the steepest descent method slow convergence of weakness, but also avoid the Newton law needs to storage and computing Hesse inverse matrix and shortcomings, Conjugate Gradient method is not only solve linear equations with most of the large method, and also one of the most effective solution large nonlinear optimization of one of the algorithm. In all kinds of optimization algorithm, the conjugate gradient method is very important. Its advantage is the storage capacity needed, it has small step convergence, high stability, and doesn t require any exotic parameters numerical experiment, this is the modern scientific computing of the answer above problem sets)

MIMO 场景下的SVD分解后，进行eigenvector预编码所获得信道容量(the capacity after deploying eigenvector beamforming)