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Questions tagged [pca]

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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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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 ...
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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
72 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 ...
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1answer
442 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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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 ...
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1answer
124 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
56 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
508 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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Principal component analysis (PCA) on convolutional network 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 ...
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1answer
154 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
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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 ...
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238 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 ...
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586 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 + \...