Questions tagged [spectral-analysis]
For questions related to Spectral analysis or Spectrum analysis is a analysis in terms of a spectrum of frequencies or related quantities such as energies, eigenvalues, etc. In specific areas it may refer to: Spectroscopy in chemistry and physics, a method of analyzing the properties of matter from their electromagnetic interactions.
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FastGAN implementation has redundant SpectralNorm followed by BatchNorm?
I am implementing a version of FastGAN, and it seems like (see the official repo) they use a Spectral norm directly followed by a Batch norm. Doesn't the spectral norm get fully cancelled by the ...
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Feature extraction from log-mel spectrograms using CNNs
I am currently working on an ASR-related project in which I would like to combine Convolutional Neural Network with GRU Network and CTC loss function.
The idea is to use the CNN to extract ...
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How to prepare audio data for deep learning?
Audio data is typically an array with the waveform represented by values from -1 to 1. There are two issues with that:
if all values are inverted, e.g. -1 becomes 1 and 1 becomes -1, the audio doesn'...
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Why should one focus on spectral operations as a computer vision researcher?
While reading about various types of mathematical operations on tensors, I encountered spectral operations for the first time.
The description is as follows (p. 53 of this book)
Spectral ops - ...
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How does graph Fourier transform work when multiple signals present on each node?
Context: I was reading the following set of notes (page 83): here and it says:
Thus, the Fourier transform of signal (or function) $ \mathbf{f} \in R^{|V|} $ on a
graph can be computed as $$ \mathbf{...
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How does Chebyshev approximation of spectral convolution work?
I was reading the following paper: here. In it, it talks about spectral graph convolutions and says:
We consider spectral convolutions on graphs defined as the
multiplication of a signal $x \in R^N$ (...
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Are spectral approaches to Graph Neural Networks still considered?
I've been reading several papers and reviews about Graph Neural Networks, and I still feel a bit confused about the difference between the two approaches, and also if the spatial approaches have ...
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What exactly is the eigenspace of a graph (in spectral clustering)?
When we find the eigenvectors of a graph (say in the context of spectral clustering), what exactly is the vector space involved here? Of what vector space (or eigenspace) are we finding the ...
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Understanding the node information score in the paper "Hierarchical Graph Pooling with Structure Learning"
The paper Hierarchical Graph Pooling with Structure Learning (2019) introduces a distance measure between:
a graph's node-representation matrix $\text{H}$, and
an approximation of this constructed ...
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