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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: | 1.0 |
Published: | 2025-07-25 |
DOI: | 10.32614/CRAN.package.hann |
Author: | Emmanuel Paradis |
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 [issues need fixing before 2025-08-25] |
Reference manual: | hann.html , hann.pdf |
Vignettes: |
Introduction to Hopfield Networks (source, R code) |
Package source: | hann_1.0.tar.gz |
Windows binaries: | r-devel: hann_1.0.zip, r-release: hann_1.0.zip, r-oldrel: hann_1.0.zip |
macOS binaries: | r-release (arm64): hann_1.0.tgz, r-oldrel (arm64): hann_1.0.tgz, r-release (x86_64): hann_1.0.tgz, r-oldrel (x86_64): hann_1.0.tgz |
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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