Noise1

说明：  此算法为最小二乘参数估计的递推算法。运行后得到辨识参数：a1= -1.4981, a2= 0.7038, b1= 1.0476, b2= 0.4704。(The algorithm for the recursive least squares parameter estimation algorithm. After operation to identify the parameters: a1 =-1.4981, a2 = 0.7038, b1 = 1.0476, b2 = 0.4704.)

说明：  采用五点差分格式解决椭圆问题，这里是3个详例。(Using a five-point difference scheme to solve elliptic problems, here are three detailed examples.)

CC_GRIDS_CONSTRAINED computes CC orders and grids satisfying a constraint.

MATLAB 实现turbo码 编解码功能，瑞利衰落信道下，高斯白噪声！(turbo encoder and decoder)

随机固定求和函数，里面附有具体的应用讲解，可参考。(Random fixed sum function, which accompanied the application of specific explanations, can be found.)

自己编写的稀疏阵列的matlab波束形成程序，可画出9阵元稀疏阵列的阵列方向图，以及相应阵列的排列示意图和同等数目阵元的均匀阵列的对比效果图(sparse array beamforming)

matlab 程序，WCDMA的程序，用MATLAB实现3G手机(SDR based MATLAB program aboutWCDMA. SDR in WCDMA)

LTE Downlink Physical Channel processing

The receiver performance is quantified by depicting the receiver operating char- acteristics (ROC) curves. This curves serve as a tool to and study the performance of a sensing scheme. ROC graphs are employed to show trade-of vs between detection probability and false alarm rates, (i.e. PD versus PFA), thus allowing the determination of an optimal threshold. To illustrate the performance of energy detectors, we generate complementary ROC curves (the average probability of miss detection $ P_{md} 1 - P_d$ versus the false alarm probability $P_f$ for different receiver structures and in different fading environments.Fig. 1 illustrates the complementary ROC curves for a single channel reception (no diversity) over AWGN channels. This figure depicts the complementary ROC curves for energy detectors.

BBABssemble(K,k,i,j,m,n)根据单元结点信(i,j,m,n)将单刚阵定位到总刚阵中。(This function assembles the element stiffness matrix k of the bilinear quadrilateral element with nodes i, j, m, and n into the global stiffness matrix K. )