PIDirPI_derinimas_3

磁盘驱动系统的有前置滤波器时系统的时间响应和整个系统的不同环节的比较(Disk drive system with pre-filter system response time and the comparison of different segments of the system)

这软件是用pisarenko方法、music方法、esprit方法来估计频率。(This software is used pisarenko way, music methods, esprit method to estimate the frequency.)

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.)

说明：  对来波方向估计,并对估计误差均方差进行估计的方法(On DOA estimation, and estimation error variance estimation methods are)

数字图像相关方法，能够处理图像的变形情况，进而得到图像的应变和切应变(Digital image correlation method, it is possible to deal with the deformation of the image, and then get the strain and shearing strain of the image)

希尔伯特-黄变换中利用EMD对一个信号进行分解，得到瞬态分量的程序(EMD for signal anaysis)

Resolucion guia 3 de Realidad Nacional Ecuatoriana

dilation of the positive part and negative part of an object based on the fuzzy bipolar mathematical morphology

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

matlab呈现混凝土孔隙分布，根据孔径大小看分布情况(Matlab shows pore distribution of concrete)