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hann: Hopfield Artificial Neural Networks

Builds and optimizes Hopfield artificial neural networks (Hopfield, 1982, <doi:10.1073/pnas.79.8.2554>). One-layer and three-layer models are implemented. The energy of the Hopfield network is minimized with formula from Krotov and Hopfield (2016, <doi:10.48550/ARXIV.1606.01164>). Optimization (supervised learning) is done through a gradient-based method. Classification is done with S3 methods predict(). Parallelization with 'OpenMP' is used if available during compilation.

Version: 1.1
Published: 2025-08-20
DOI: 10.32614/CRAN.package.hann
Author: Emmanuel Paradis ORCID iD [aut, cre, cph]
Maintainer: Emmanuel Paradis <Emmanuel.Paradis at ird.fr>
BugReports: https://github.com/emmanuelparadis/hann/issues
License: GPL-3
URL: https://github.com/emmanuelparadis/hann
NeedsCompilation: yes
CRAN checks: hann results

Documentation:

Reference manual: hann.html , hann.pdf
Vignettes: Introduction to Hopfield Networks (source, R code)

Downloads:

Package source: hann_1.1.tar.gz
Windows binaries: r-devel: hann_1.1.zip, r-release: hann_1.1.zip, r-oldrel: hann_1.1.zip
macOS binaries: r-release (arm64): hann_1.1.tgz, r-oldrel (arm64): hann_1.1.tgz, r-release (x86_64): hann_1.1.tgz, r-oldrel (x86_64): hann_1.1.tgz
Old sources: hann archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=hann to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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