Admittancematrix

some example for matlab

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. )

SLNR下，信噪比和误码率的关系,涉及了两域联合(SLNR, the relationship between SNR and bit error rate, involves a two-domain joint )

利用matlab将输入的rgb图像转化为灰度图像后，利用阈值求的二值图像，边缘算子求的边缘图像，边缘图像求归一化不变矩，Hu矩。(Matlab input rgb image to grayscale image, using the binary image threshold seeking child seeking the edge of the image, the edge operator, the edge of the image seeking normalized invariant moments, Hu moments.)

一个能够与Trnsys联合运行的增量式PID的m文件里面有中英混合说明。(An incremental PID Trnsys jointly run the m file inside the mixed.)

MVDR Beamforming wher in the interference direction null s put and the signal in the intended direction is maximised. The plots the beamformer response

使用MATLAB来编写fft快速算法的具体实现方法的源码。(Use MATLAB to write fft Fast Algorithm for the concrete implementation method of the source code.)

经典的基于短时能量和短时平均过零率的双门限检测方法(Classic double threshold detection method based on short-time energy and short-time average zero crossing rate)

贝叶斯分类算法是统计学的一种分类方法，它是一类利用概率统计知识进行分类的算法。在许多场合，朴素贝叶斯(Naï ve Bayes，NB)分类算法可以与决策树和神经网络分类算法相媲美，该算法能运用到大型数据库中，而且方法简单、分类准确率高、速度快。(Bayesian classification algorithm is a statistical classification method, which is a kind of knowledge to classify the use of probabilistic algorithms. In many cases, Naive Bayes (Naï ve Bayes, NB) classification algorithm with decision trees and neural network classification algorithm is comparable, the algorithm can be applied to large s, and the method is simple, accurate classification rate of speed.)

RADAR scateriing using pulse compression principle