/explore

Click through on any links that interest you or select the planets on the right to continue exploring the Outer Web.
You are here

 bartwronski.com
Comparing images in frequency domain. "Spectral loss" - does it make sense? | Bart Wronski
| | therealmjp.github.io
Signal Processing Primer
4.0 parsecs away

Travel
| | For a theoretical understanding of aliasing and anti-aliasing, we can turn to the fields of signal processing[1] and sampling theory[2]. This article will explain some of the basics ofthese two related field in my own words, taking a more theoretical point of view. In the following article the concepts covered here will be used to analyze common aspects of real-time graphics, so that we can describe them in terms of signal processing.
| | sander.ai
Diffusion is spectral autoregression - Sander Dieleman
2.9 parsecs away

Travel
| | A deep dive into spectral analysis of diffusion models of images, revealing how they implicitly perform a form of autoregression in the frequency domain.
| | blog.demofox.org
Why Can't You Design Noise in Frequency Space? « The blog at the bottom of the sea
4.7 parsecs away

Travel
| | The python code that goes along with this blog post can be found at https://github.com/Atrix256/InverseDFTProblems To evaluate the quality of a blue noise texture, you can analyze it in frequency space by taking a discrete Fourier transform. What you want to see is something that looks like tv static (white noise) with a darkened center,...
| | www.unofficialgoogledatascience.com
Fitting Bayesian structural time series with the bsts R package
44.8 parsecs away

Travel
| by STEVEN L. SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data scien...