多维随机数的生成方法

berkeley加州大学SAP系列软件之SolidSAP，由Edward L.Wilson教授开发的三维结构源程序，功能强大，代码清晰，含学习手册。(SolidSAP, a three-dimensional structure source program developed by Professor Edward L. Wilson, is a software of the SAP series at the University of California, Berkeley. It has powerful functions, clear code and learning manual.)

对大量数据的差值与拟合算法的Matlab实现，基于多用思想(The difference of large amounts of data fitting algorithm of the Matlab implementation, based on multi-thinking)

《矩阵论导教.导学.导考》。是程云鹏《矩阵论》的课后习题答案与复习题纲()

说明：  非常好的卡尔曼滤波学习程序。文章中有原题，有解题步骤，有实现程序。适合卡尔曼学习过程中的人。(Very good learning process Kalman filter. The article in the original title, there are problem-solving steps to achieve the procedure. Kalman learning process for people.)

使用labview2009开发平台，实现对机械信号频谱泄露的功能。(Use labview2009 development platforms for the mechanical function of the signal spectrum leakage.)

％ 奇异值分解 (sigular value decomposition,SVD) 是另一种正交矩阵分解法；SVD是最可靠的分解法， ％ 但是它比QR 分解法要花上近十倍的计算时间。[U,S,V]=svd(A)，其中U和V代表二个相互正交矩阵， ％ 而S代表一对角矩阵。 和QR分解法相同者， 原矩阵A不必为正方矩阵。 ％ 使用SVD分解法的用途是解最小平方误差法和数据压缩。用svd分解法解线性方程组，在Quke2中就用这个来计算图形信息，性能相当的好。在计算线性方程组时，一些不能分解的矩阵或者严重病态矩阵的线性方程都能很好的得到解( Singular value decomposition (sigular value decomposition, SVD) is another orthogonal matrix decomposition method SVD decomposition is the most reliable method, but it takes more than QR decomposition near ten times the computing time. [U, S, V] = svd (A), in which U and V on behalf of two mutually orthogonal matrix, and the S on behalf of a diagonal matrix. And QR decomposition are the same, the original matrix A is no need for the square matrix. The use of SVD decomposition method are used as a solution of least squares error method and data compression. Using SVD decomposition solution of linear equations, in Quke2 on to use this information to calculate the graphics performance quite good. In the calculation of linear equations, some indecomposable matrix or serious pathological matrix of linear equations can be a very good solution)

针对功放得到非线性失真，采用查表法预失真对功放的非线性进行补偿，仿真表明了补偿方式的有效性。(Obtained for nonlinear distortion amplifier, using the look-up table predistortion to compensate for non-linear power amplifier, simulation shows the effectiveness of compensation.)

based classification (SRC) has been widely used for face recognition (FR). SRC first codes a testing sample as a sparse linear combination of all the training samples, and then classifies the testing sample by evaluating which class leads to the minimum representation error. While the importance of sparsity is much emphasized in SRC and many related works, the use of collaborative representation (CR) in SRC is ignored by most literature.

说明：  恒模算法的简介，它适用于信道的盲均衡。Matlab程序提供基本的框架，可以修该里面的参数以测试该算法的性能(CMA briefings, which applies to Channel Blind balanced. Matlab to provide a basic framework, it can be done inside of the parameters to test the performance of the algorithm)

说明：  能够实现线性回归,里面有一个线性回归的实例(It can realize linear regression. There is an example of linear regression)