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Questions tagged [svd]

Singular Value Decomposition (SVD) is a factorization of a real or complex matrix, with many useful applications in signal processing and statistics.

The Singular Value Decomposition (SVD) of a rectangular matrix A is a decomposition of the form:

A = U S V*

where U and V are orthogonal matrices, and S is a diagonal matrix containing the singular values.

In scientific software for statistical computing, function svd computes this decomposition.

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extracting watermark svd matlab

I have a problem extracting watermark using SVD. Here is my code: clc close all; a=0.0010 I=imread('citra.jpg'); %Image Host I=rgb2gray(I); II=im2double(I); [U,S,V]=svd(II); M=imread('logoUPN.jpg'); %Image…
Ghora
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Recommender Systems: Does using Singular Value Decomposition rule out the possibility of using Euclidean Distance as way of measuring similarity?

I'm learning about recommender systems and learning about different similarity algorithms. Euclidean distance would change as the scale of the objects being compared changes. In that case, would SVD (Singular Value Decomposition) and Euclidean…
covfefe
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Truncated SVD implementation in Java

I need the Truncated SVD implementation in java. I need to pass a matrix of doubles and an integer value representing the rank where to filter out noise. In output i need a filtered matrix of doubles. Is there something ? Thank you
vincenzodentamaro
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How to use output of TruncatedSVD() as input to neural network?

I have a dataset(contains sentences) on which I need to perform vectorization and then dimensionality reduction through TruncatedSVD() to reduce no. of features to 100. Then i want to use that svd output as input to neural network. But i cannot…
BISHAL Adhikari
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I cannot see the plot of my points in R

I am trying to plot a u vector using the R language. I have obtained U throught SVD applied to some training data. I have downloaded the useful library for tm and ggplot2. I want to plot the 2 dimensions of the vector U , which results from SVD of…
Marzo
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How to fix this PCA in R

I am creating a PCA plot from data: label <- read.table('label_clusters.tsv') mydata <- read.table('raw_clusters.tsv') GP.svd = svd(mydata) dat = data.frame("pc1"= GP.svd$u[,1], "pc2"= GP.svd$u[,2], "Data"= c(rep("my",…
cncx
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Different order of eigenvalues computed with PCA and SVD

I really don't know why, when i computed the eigenvalues with PCA from my dataset i obtain a vector which have values in different order respect of SVD This is the result This is the code Thanks for help!!!
FraMan
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Eigen SVD strange failure in Google test

I'm executing next code in google test TEST(LinearALgebra, SVD) { Eigen::Matrix3d m; m << -0.0793311, 0.999997, -1.17221e-07, 1.74, 0.00249557, 0.000445095, 9.88131e-324, 0.000191222, -0.000284459; Eigen::Matrix3d…
Mike
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Singular Value Decomposition positive value

I am using Singular Value Decomposition (SVD) applied to Singular Spectrum Analysis (SSA) of a timeseries. % original time series x1= rand(1,10000); N = length(x1); % windows for trajectory matrix L = 600; K=N-L+1; % trajectory matrix/matrix of…
gabboshow
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fixed point singular value decomposition in c/c++

I am looking for some c/c++ libraries to do fixed point singular value decomposition or eigenvalue decomposition. Do you know any libraries or any pointers to existing codes? Thanks
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