main_16QAM

Beyond software architecture

Fminsearch不承认的约束限制。 不过简单的转换方法存在 转换成一个绑定的约束问题 无约束问题。 Fminsearchbnd用于酷似fminsearch， 除了边界应用到变量。 应用于国内的界限，利用 改造中的变量。 （二次型 单式，双罪恶界（十）。） 具有包容性的不平等的界限，它承认 边界值本身，但不准 在所有函数之外的范围评估。 请注意，fminsearchbnd允许用户准确地固定在某个给定值通过设置一个变量的确切范围相同的值。 (Fminsearch does not admit bound constraints. However simple transformation methods exist to convert a bound constrained problem into an unconstrained problem. Fminsearchbnd is used exactly like fminsearch, except that bounds are applied to the variables. The bounds are applied internally, using a transformation of the variables. (Quadratic for single bounds, sin(x) for dual bounds.) The bounds are inclusive inequalities, which admit the boundary values themselves, but will not permit ANY function evaluations outside the bounds. Note that fminsearchbnd allows the user to exactly fix a variable at some given value, by setting both bounds to the exact same value. )

包含剪切波变换（以拉普拉斯金字塔变换为尺度剖分），以及该变换的压缩感知重构测试应用程序。(Contains shear wave transform (Laplace pyramid transform for the scale subdivision), as well as the transformation of compressed sensing reconstruction test application.)

功率控制函数代码描述细节。博弈论的应用。。。。。。。。。。。(Power Control)

This paper investigates the generalized Pars ’s theorem of fractional Fourier transform (FRFT) for concentrated data. Also, in the framework of multiple FRFT domains, Pars ’s theorem reduces to an inequality with lower and upper bounds associated with FRFT parameters, named as generalized Pars ’s theorem by us. These results theoretically provide potential valuable applications in filtering, and examples of filtering for LFM signals in FRFT domains are demonstrated to support the derived conclusions

Function to compute the Karhunen-Loeve Transform (KLT) on an ensemble of 1-D signals,

基于matlab的SOM神经网络源码,讲解matlab下如何实现SOM神经网络，给出实例(SOM—ANN source code based on matlab)

对图像进行方向滤波,可以消除图像中有规律的网格或者直线干扰(direction filter)

自行编写的加入噪声估计的KSVD去噪算法，利用SVD分解进行噪声估计( KSVD denoising algorithm to prepare the addition of noise estimation, the use of SVD decomposition noise estimation )

用matlab实现支持向量机分类算法，通过对数据进行测试训练来进行分类(Using matlab implementation support to the classification algorithms to data, through testing and training to categorize )