psk

This shows that relay power is an important criterion which decides the gain we get from simple relaying as compared to direct transmission.

提供一种新型自适应滤波器的设计方法，能自由设计参数！(To provide a new type of adaptive filter design methods, design parameters can be freely!)

说明：  生存分析，学习总结资料和SAS实验.ppt(Survival analysis, study summarizes experimental data and SAS. Ppt)

说明：  遗传算法用于求函数最大值，可以修改函数名和迭代次数(A function of genetic algorithm is used to seek the maximum, you can modify the function name and the number of iterations)

该代码是lte中的winner信道模型的源代码，该模型是现在流行的信道模型(The code is a winner lte channel model in the source code, the model is now a popular channel model)

小波变换matlab程序,实现小波变换的程序(Wavelet transform matlab process procedures for the realization of wavelet transform)

Consultantr assistance system to help manage client

this book speak to matlab

《MATLAB数值计算案例分析》，内含各种源码，运用MATLAB解决各种数值计算问题。( Case analysis MATLAB numerical calculation, containing all the source code, using MATLAB to solve a variety of numerical calculation problems.)

MATLAB 牛顿下山法的一个小程序，原理就不详细说了。因牛顿迭代法受初值选取的限制，为防止迭代发散，对迭代过程再附加一项要求:|f(x(k+1))|<|f(x(k))|,将牛顿法迭代的结果:x(k+1) =x(k)-f(x(k))/f (x(k))和前一近似值x(k)适当加权平均做为新的改进值:x(k+1)=u*x(k+1) +(1-u)*x(k),其中u(0<> 迭代时u取1开始，逐次减半计算，直至附加要求符合为止。实例计算中x(k)=x(0)不变，只更新u和x(k+1)，直至:|f(x(k+1))|<|f(x(k))|（即|f(x(1))|<|f(x(0))|)，然后更新下山因子为u=1,继续以牛顿法迭代。(MATLAB Newton-down a small program, the principle is not explained in detail. Newton iteration by the initial value of the selected limit, in order to prevent additional iterative divergence, the iterative process a request: | f (x (k+1)) | < | f (x (k)) | Newton iteration Results: x (k+1) ' = X (k)-f (x (k))/f' (x (k)) and a previous approximation x (k), appropriately weighted average as a new improved value: x (k+1 ) = u* x (k+1) ' + (1-u)* x (k), where u (0 < u> iteration take successive calculated at 50 until the additional requirements found so far. examples of calculation of X ( k) = x (0) unchanged profile u and x (k+1, hungry) until: | f (x (k+1)) | < | f (x (k)) | (i.e. | f (x (1)) | < | f (x (0)) |), then profile downhill factor for u = 1, to continue to Newton iteration.)