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Description: This a matlab code for right eigen vector and left eigen vector for power system-This is a matlab code for right eigen vector and left eigen vector for power system
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Size: 1024 |
Author: mahesh |
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Description: c code to calculate the eigen vector
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Size: 61440 |
Author: kiran |
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Description: 用于本征值与本征向量计算的程序，可以直接调用-For the intrinsic value and eigen vector calculation procedure can be directly invoked
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Size: 262144 |
Author: 韩浩东 |
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Description: Complete linear algebra, especially Eigen-value and eigen-vector
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Size: 1543168 |
Author: Lee |
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Description: eigen value, eigen vector, eigen space.
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Size: 3072 |
Author: James |
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Description: 针对多径效应的影响，提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号，采用单样本数信号矢量构造了一个前后向矩阵束，并利用两个酉矩阵对该矩阵束进行降维处理，最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵，可在低
信噪比和单样本数情况下，有效地克服多径效应，实现同时多目标低仰角估计，相比最大似然算法，避免了谱峰搜索，计算量小。仿真结果验证了该算法的有效性。-To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method
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Size: 254976 |
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Description: Eigen value - Eigen vector - Matlab code
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Size: 1024 |
Author: amir |
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Description: Function to implement Linear Discriminant Analysis
Usage:-
[Xnew,V,mX,D] = lda(X,index,mX)
[V,D] = lda(X,index)
where:-
X = concatenated grand profile vectors (GPV)
i = class index of each vector
Xnew = new feature vectors
P = eigen vectors
mX = mean of GPV (optional in input)
D = eigen values- Function to implement Linear Discriminant Analysis
Usage:-
[Xnew,V,mX,D] = lda(X,index,mX)
[V,D] = lda(X,index)
where:-
X = concatenated grand profile vectors (GPV)
i = class index of each vector
Xnew = new feature vectors
P = eigen vectors
mX = mean of GPV (optional in input)
D = eigen values
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Size: 1024 |
Author: Praveen |
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Description: Function to perform Principle Component Analysis over a set of training
vectors passed as a concatenated matrix.
Usage:- [V,D,M] = pca(X,n)
[V,D] = pca(X,aM,n)
where:-
<input>
X = concatenated set of column vectors
aM = assume that the mean is aM
n = number of principal components to extract (optional)
<output>
V = ensemble of column eigen-vectors
D = vector of eigen-values
M = mean of X (optional)
- Function to perform Principle Component Analysis over a set of training
vectors passed as a concatenated matrix.
Usage:- [V,D,M] = pca(X,n)
[V,D] = pca(X,aM,n)
where:-
<input>
X = concatenated set of column vectors
aM = assume that the mean is aM
n = number of principal components to extract (optional)
<output>
V = ensemble of column eigen-vectors
D = vector of eigen-values
M = mean of X (optional)
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Size: 1024 |
Author: Praveen |
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Description: 运用插值的全矢量有限差分法求解阶跃光波导本征模式以及等效折射率
-Using the interpolation of full vector finite difference method to solve step eigen mode optical waveguide and equivalent refractive index
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Size: 3072 |
Author: liam |
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Description: This file takes cropped yale face images file as input and performs classifications based on
1. Correlation
2. Eigen vector based classification (Eigen Face)
3. Fisher Linear Discriminator (FLD) (Fisher Face)
The zip contains two files
readyaledata.m to read the image database
EigenFace-FisherFace.m to do classification as described above
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Size: 3072 |
Author: Abdul Maalik |
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Description: a graphical output that displays total energy, the potential energy function, kinetic energy function, eigen vector and probability distribution for a given quantum state n
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Size: 1024 |
Author: kezalo |
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Description: eigen value vector representation
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Size: 620544 |
Author: simran |
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Description: All that it guaranties is that all points on that wave have a definite relative amplitude. So, that is the beauty of the mode shape the mode shape does not dictate the absolute value of the deflection. Similarly you can do it for all of them and you can normalize these Eigen vectors, you have studied them. Commonly what we do is we take one of them, the top one you make it to unity and scale the others. But there are other ways of scaling and once you normalized it you call it an orthonormal Eigen vector.-All that it guaranties is that all points on that wave have a definite relative amplitude. So, that is the beauty of the mode shape the mode shape does not dictate the absolute value of the deflection. Similarly you can do it for all of them and you can normalize these Eigen vectors, you have studied them. Commonly what we do is we take one of them, the top one you make it to unity and scale the others. But there are other ways of scaling and once you normalized it you call it an orthonormal Eigen vector.
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Size: 727040 |
Author: Ritika |
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Description: Eigen 3.2.2帮助文档。Eigen是一个高层次的C ++库，有效支持线性代数，矩阵和矢量运算，数值分析及其相关的算法。-Eigen 3.2.2 Help documentation. Eigen is a high-level C++ library, effective supports linear algebra, matrix and vector operations, numerical analysis and related algorithms.
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Size: 4478976 |
Author: zhang |
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Description: eigen vector detector cognitive radio
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Size: 1024 |
Author: SARIKA DEVI |
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Description: C++实现矩阵的SVD分解，矩阵基本运算“+，-，*，/”，三角分解，QR分解，矩阵显示，矩阵转置，矩阵特征值与特征向量运算.
并在 Source.cpp中附有使用例子代码，方便读者快速上手。
经本人测试，完全可以运行，放心使用。
对于SVD分解，经过与matlab中结果对比，发现，当矩阵的列数>=行数时，基本没问题。(Using C++ language realizes the SVD decomposition of matrix,as well as the basic operation of matrix "+, -, *, /", triangular decomposition, QR decomposition, matrix display, matrix transpose, matrix eigen value and eigen vector operation.
And in Source.cpp, how to use these code was supplied, which is very convenient for you to quickly use these codes into your programming.
For SVD decomposition, I had compare the result with that of MATLAB,and I found that when the columns of the matrix number > = line number,my code has no problem.)
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Size: 30720 |
Author: 东篱
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Description: C++ 矩阵操作， ROS，Eigen3(C++ Library manipulating Vector Matrix)
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Size: 3050496 |
Author: Akis
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