Add citation information

CITATION.cff

@@ -0,0 +1,11 @@
+cff-version: 1.1.0
+message: "If you use this software, please cite it as below."
+authors:
+- family-names: René
+  given-names: Alexandre
+orcid: https://orcid.org/0000-0003-3795-5073
+title: "Solid colored noise using sparse convolutions"
+version: v0.1.0
+doi: 10.5281/zenodo.12802822
+date-released: 2024-07-23
+url: "https://github.com/alcrene/colored-noise"

README.md

@@ -8,6 +8,8 @@ The sparse convolution algorithm is an effective way to generate a noise signal,
 
 For more information on how this works, see the [doc page](https://alcrene.github.io/colored-noise).
 
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.12802822.svg)](https://doi.org/10.5281/zenodo.12802822)
+
 ## Design goals & usage
 
 In applications, often we characterize signals by their autocorrelation function; when we want to characterize them by a single number, that number is generally the *correlation time*, describing the width the of autocorrelation function. Computing the autocorrelation function for a given stochastic system is often a difficult analytical problem. Therefore, an algorithm which promises to solve the *inverse* problem – going from autocorrelation function to a noise – is a valuable tool in the practitioner’s toolkit. This is what the sparse convolution algorithm purports to offer.