all-emd

实现mimo预编码环境中容量的所有计算,包括不同的准则(mimo achieve pre-coding capacity of the environment all calculations, including the different criteria)

sar图像去噪的几种新的方法，从先验概率中采样，计算权重，二维声子晶体FDTD方法计算禁带宽度的例子。( Several new methods sar image denoising, Sampling a priori probability, calculate the weight, Dimensional phononic crystals FDTD method calculation examples band gap.)

unlock v79 by sound track

说明：  机械优化设计黄金分割法和三次插值法，适用于无约束一维极值问题(Optimal Design of Mechanical golden section method and the cubic interpolation method, applied to non-binding one-dimensional extremum problem)

基于前人读取LIDAR数据并且显示给与解释和增加写内容 (LIDAR data based on previous reads and displays content to give explanations and to increase writing)

QAM调制解调的实现，误码率分析，眼图，各个滤波器的性质(QAM modulation and demodulation implementation, bit error rate analysis, eye pattern, the nature of the various filters)

恒虚警率目标检测,计算雷达影像CFAR 阈值，达到雷达影像目标检测的目的(calculates classical radar CFAR threshold for 0-mean AWGN.classical Neyman-Pearson detection threshold for radar detection under additive Gaussian white noise criterion and specifid false alarm probability.)

MUSIC算法[1]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 algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)

短时傅里叶变换的matlab函数，有助于理解算法原理(Short-time Fourier transform matlab function, help to understand the algorithm principle)

matlab中用不同的方法计算随机数列的功率普(matlab using different methods of calculating the random numbers out of power )