@article{93df4678ced24b4bbed73cb318f22890,
title = "On Guaranteed Correction of Error Patterns with Artificial Neural Networks",
abstract = "In this paper, we analyze applicability of singleand two-hidden-layer feed-forward artificial neural networks, SLFNs and TLFNs, respectively, in decoding linear block codes. Based on the provable capability of SLFNs and TLFNs to approximate discrete functions, we discuss sizes of the network capable to perform maximum likelihood decoding. Furthermore, we propose a decoding scheme, which use artificial neural networks (ANNs) to lower the error-floors of low-density parity-check (LDPC) codes. By learning a small number of error patterns, uncorrectable with typical decoders of LDPC codes, ANN can lower the error-floor by an order of magnitude, with only marginal average complexity incense.",
keywords = "Error-floors, Linear block codes, Low-density parity-check codes, Ml decoding., Neural networks",
author = "Sr{\d}an Brki{\'c} and Predrag Ivani{\v s} and Bane Vasi{\'c}",
note = "Funding Information: This work was supported by the Science Fund of the Republic of Serbia under project LIDA (no. 6462951) and the Serbian Ministry of Science under project TR32028. Funding Information: ACKNOWLEDGMENT This work was supported by the Science Fund of the Republic of Serbia under project LIDA (no. 6462951) and the Serbian Ministry of Science under project TR32028. Bane Vasic acknowledges support of the NSF under grants CIF-1855879, CCF-2100013, CCSS-2027844 and CCSS-2052751, as well as the support of the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration and funded through JPL{\textquoteright}s Strategic University Research Partnerships (SURP) Program. Bane Vasic has disclosed an outside interest in Codelucida to the University of Arizona. Conflicts of interest resulting from this interest are being managed by The University of Arizona in accordance with its policies. Publisher Copyright: {\textcopyright} 2022,Telfor Journal. All Rights Reserved.",
year = "2022",
doi = "10.5937/telfor2202051B",
language = "English (US)",
volume = "14",
pages = "51--55",
journal = "Telfor Journal",
issn = "1821-3251",
publisher = "Academic Mind",
number = "2",
}