LMS

基于傅里叶变换和匹配追踪的信号分解的一种新方法(Based on FFT and MP signal decomposition)

无线通信系统中,信道间的相关性随着天线数目的增加而减小,当趋于无穷时,可视为正交.此为这一观点的仿真程序.(In wireless communication system, the correlation between channel and decreased as the number of antennas, when becomes infinite, can be treated as orthogonal. This a simulation program for this view.)

PermanentMagnetSynchronousMachine,model and simulaltion

cubic spline code information

This file is a literature survey of password authentication

MATLAB 设计的一个关于用户界面的例子(MATLAB design a user interface example)

可以完成地震记录的合成，实现地震记录的正演模拟(Synthetic seismogram can be done to achieve forward modeling of seismic records)

1 SIFT 发展历程 SIFT算法由D.G.Lowe 1999年提出，2004年完善总结。后来Y.Ke将其描述子部分用PCA代替直方图的方式，对其进行改进。 2 SIFT 主要思想 SIFT算法是一种提取局部特征的算法，在尺度空间寻找极值点，提取位置，尺度，旋转不变量。 3 SIFT算法的主要特点： a) SIFT特征是图像的局部特征，其对旋转、尺度缩放、亮度变化保持不变性，对视角变化、仿射变换、噪声也保持一定程度的稳定性。 b) 独特性(Distinctiveness)好，信息量丰富，适用于在海量特征数据库中进行快速、准确的匹配[23]。 c) 多量性，即使少数的几个物体也可以产生大量SIFT特征向量。 d) 高速性，经优化的SIFT匹配算法甚至可以达到实时的要求。 e) 可扩展性，可以很方便的与其他形式的特征向量进行联合。 4 SIFT算法步骤： 1） 检测尺度空间极值点 2） 精确定位极值点 3） 为每个关键点指定方向参数 4） 关键点描述子的生成 本包内容为sift算法matlab源码(1 SIFT course of development SIFT algorithm by DGLowe in 1999, the perfect summary of 2004. Later Y.Ke its description of the sub-part of the histogram with PCA instead of its improvement. 2 the SIFT main idea The SIFT algorithm is an algorithm to extract local features in scale space to find the extreme point of the extraction location, scale, rotation invariant. 3 the main features of the SIFT algorithm: a) SIFT feature is the local characteristics of the image, zoom, rotate, scale, brightness change to maintain invariance, the perspective changes, affine transformation, the noise also maintain a certain degree of stability. b) unique (Distinctiveness), informative, and mass characteristics database for fast, accurate matching [23]. c) large amounts, even if a handful of objects can also produce a large number of SIFT feature vectors. d) high-speed and optimized SIFT matching algorithm can even achieve real-time requirements. e) The scalability can be very convenient fe)

Systematic biases in early ERP and ERF components as a result of high-pass filtering

由于通常的通信信道的冲激响应的稀疏性，使得NLMS算法的收敛速度还有待提高。所以，近年来，有学者提出了成比例的归一化的均方误差算法(PNLMS)。PNLMS在自适应过程的开始阶段有着很快的收敛的速度，但是迭代过程越往后，收敛速度越慢。于是，众多学者提出了许多的改进算法。本程序是通过matlab仿真对近年来流行的PNLMS,IPNLMS,MPNLMS等算法进行的仿真程序(As usual communication channel impulse response sparse, making the convergence rate of NLMS algorithm to be improved. Therefore, in recent years, some scholars have proposed a proportional to the normalized mean square error algorithm (PNLMS). PNLMS the beginning of the adaptive process has a fast convergence speed, but the more backward iterative process, convergence slower. Thus, many scholars have made many improvements in algorithms. Matlab simulation of this program is popular in recent years PNLMS, IPNLMS, MPNLMS other algorithms of the simulation program)