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Questions tagged [pca]

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Reconstruct images from PCA reduced dimensions with NN

I was reading this Medium post and I had the idea to reconstruct the original images with a convolutional neural network instead of applying the inverse transform method. The problem is that I don't ...
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1answer
102 views

Principal Component Analysis definition

I have just learned about this method, so I am not very familiar with it. As far as I know, Principal Component Anlysis (aka PCA) is used to transform a vector $x$ that belongs to a space of $d$ ...
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4answers
258 views

Apply Principal Component Analysis for RGB Images

I've implemented a method to compute PCA on grayscale images. I haven't seen PCA on RGB images yet, which left me wondering if it is possible to perform it. With RGB images, is PCA done for each ...
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0answers
15 views

How would PCA run on multivariate time-series data affect phase relationships across variables?

I am running PCA on a multivariate time-series dataset using observations across time (i.e. w/out time as an explicit variable) as the design matrix. Given this setup, I've found that it is difficult ...
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0answers
32 views

Implementation of PCA for hyper-spectral Image Processing

I have been studying the concept of PCA and its implementation for dimensionality reduction for more than 1 month. My goal is to classify a hyperspectral image using sparse representation by the ...
2
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0answers
38 views

Is it possible to weight the high frequency components of a signal to give high frequecy components greater overall power in the total signal?

I have a multivariate time-series dataset, and would like to run PCA on my dataset to reduce the number of variables I input into a time-series model. I am concerned that running PCA may end up ...
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1answer
191 views

How Can PCA Be Used in Image Analysis [closed]

I am still a not how PCA can be used in image analysis and where is it is mostly used. For example how can PCA be used in order to differentiate between different faces? Can you please mention other ...
2
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1answer
750 views

What Is the Difference Between PCA and Karhunen Loeve (KL Transform)?

I have been reading about Karhunen-Loeve or also known as KL transform and I see that when it is used to reduce dimension the procedure is identical to PCA, that is, for both methods the covariance ...
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0answers
32 views

Sourse separation from known underdetermined mixing matrix

How to recover uncorrelated N sources from given N-1 signals and known mixing matrix M, (e.g. 9x8 matrix)? If I just use pseudo-inverse matrix M+, my source estimates are correlated with each other ...
0
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1answer
149 views

Finding filaments in an image

I am at the moment working on images such as this one: What you see are filamentous structures / bundles. Other images coming from slightly different experiments could have more sparse / thick / ...
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1answer
60 views

How to express one image in terms of another one

I have two (black and white) images of identical size - let's say 128x128 pixels. I'm interested in expressing Im2 in terms of ...
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1answer
580 views

PCA to reduce dimensionality to 99% variance

I'm attempting to use PCA to reduce the dimensionality of a dataset I have. I want to explain 99% of the variance in the dataset, and I think I've been able to determine that, but I'm unsure what I ...
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3answers
2k views

Principal Component Analysis (PCA) on Convolutional Neural Network (CNN) Features

Please, I have a question regarding PCA and features which are extracted from a convolutional layer. link if we have a test dataset , and we extract all conv features of all images at test dataset ...
2
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1answer
173 views

Whitening signal vs. whitening its DFT

A whitening transformation (PCA) is simply a rotation into a space in which variables become uncorrelated. Because a DFT is a transformation into a coordinate space of orthogonal frequency components,...
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2answers
44 views

Face Classification. Is it OK to only use geometric features?

I am trying to teach myself the basics of facial recognition. I see that some resources use just distances between some points on the face (e.g., distance between 2 eyes, eyes to nose, etc). Some ...
1
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1answer
266 views

What Is the Significance of a Large Residual When Applying Principal Component Analysis?

I am using Matlab function PCA (principal component analysis) to reduce the dimensionality of a data set with approximately 20 000 observations x 100 dimensions. After having obtained the principal ...
4
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2answers
683 views

MUSIC algorithm derivation

Setup Suppose we have a complex $L\times 1$ signal $\mathbf{x}$ with two tones at (unknown) frequencies and phases defined as: $$ x_n = A_1 e^{j \omega_1n + \varphi_1} + A_2 e^{j \omega_2n + \...