WaveletNet

基于DWT及DCT的数字水印的代码，该改代码是分开形式给出，具体结果自己可以运行试试，很不错的(key word is DWT AND DCT ,if you are interested in it ,you can call me ,we can talk about it.)

对给定的长方矩阵用两种方法求其广义逆矩阵,分析其运算量。(Given its rectangular matrix generalized inverse matrix.)

说明：  NOMA的吞吐量的计算，可以正确计算出结果。实测有效。(The throughput of NOMA can be calculated correctly. The measured results are effective.)

无线通信信道的自适应均衡算法，RLS算法，有助于消除码间串扰(Wireless communication channel adaptive equalization algorithm, RLS algorithm, help to eliminate ISI)

DNG simulation using fdtd in matlab code

matlab函数、命令集 一共有几百条，按字母索引(matlab function, command set)

MUSIC算法是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。MUSIC算法就是利用这两个互补空间之间的正交特性来估计空间信号的方位。噪声子空间的所有向量被用来构造谱，所有空间方位谱中的峰值位置对应信号的来波方位。MUSIC算法大大提高了测向分辨率，同时适应于任意形状的天线阵列，但是原型MUSIC算法要求来波信号是不相干的。(MUSIC algorithm is a matrix decomposition method based on feature space. From the geometric point of view, the observed spatial signal processing can be decomposed into signal subspace and noise subspace, it is clear that the two spaces are orthogonal. The signal received by the array to the subspace of the covariance matrix of the signal component corresponding eigenvectors, the noise subspace of the covariance matrix of all by the smallest eigenvalue (noise variance) eigenvectors corresponding to the composition. MUSIC algorithm is the use of orthogonal properties between these two complementary space to estimate the spatial orientation of the signal. Noise subspace of all vectors are used to construct the spectrum, all the spatial orientation of the spectrum corresponding to the peak position of the signal wave direction. MUSIC algorithm greatly improves the resolution measurements, while the antenna array adapted to any shape, but the prototype MUSIC algorithm requires to wave sign)

This Fact device (SSSC) ready to help

matlab飞机轨迹自动生成程序，网友可根据自己需求 更改轨迹(trajectory of aircraft programe)

模糊层次分析法的程序实现，score 三个表是别人的打分表，填进去 然后在matlab直接调用[S1,S2,S3] = Matrix() 然后再调用 C = firstFuzzy( S1, S2, S3 )这个就可以了 出来的就是打分表的所得的权重((1, S2, S3) = Matrix () and then call C = firstFuzzy (S1, S2, S3) This is the same as the other one of the scoring tables. It can be out of the scoring table is the weight of the income)