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Novel random k Satisfiability for k ≤ 2 in hopfield neural network

The k Satisfiability logic representation (kSAT) contains valuable information that can be represented in terms of variables. This paper investigates the use of a particular non-systematic logical rule namely Random k Satisfiability (RANkSAT). RANkSAT contains a series of satisfiable clauses but t...

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主要な著者: Saratha Sathasivam,, Mohd. Asyraf Mansor,, Ahmad Izani Md Ismail,, Siti Zulaikha Mohd Jamaludin,, Mohd Shareduwan Mohd Kasihmuddin,, Mustafa Mamat,
フォーマット: 論文
言語:English
出版事項: Penerbit Universiti Kebangsaan Malaysia 2020
オンライン･アクセス:http://journalarticle.ukm.my/16014/1/23.pdf
http://journalarticle.ukm.my/16014/
https://www.ukm.my/jsm/malay_journals/jilid49bil11_2020/KandunganJilid49Bil11_2020.html
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id my-ukm.journal.16014
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spelling my-ukm.journal.160142020-12-17T05:18:30Z http://journalarticle.ukm.my/16014/ Novel random k Satisfiability for k ≤ 2 in hopfield neural network Saratha Sathasivam, Mohd. Asyraf Mansor, Ahmad Izani Md Ismail, Siti Zulaikha Mohd Jamaludin, Mohd Shareduwan Mohd Kasihmuddin, Mustafa Mamat, The k Satisfiability logic representation (kSAT) contains valuable information that can be represented in terms of variables. This paper investigates the use of a particular non-systematic logical rule namely Random k Satisfiability (RANkSAT). RANkSAT contains a series of satisfiable clauses but the structure of the formula is determined randomly by the user. In the present study, RANkSAT representation is successfully implemented in Hopfield Neural Network (HNN) by obtaining the optimal synaptic weights. We focus on the different regimes for k ≤ 2 by taking advantage of the non-redundant logical structure, thus obtaining the final neuron state that minimizes the cost function. We also simulate the performances of RANkSAT logical rule using several performance metrics. The simulated results suggest that the RANkSAT representation can be embedded optimally in HNN and that the proposed method can retrieve the optimal final state. Penerbit Universiti Kebangsaan Malaysia 2020-11 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/16014/1/23.pdf Saratha Sathasivam, and Mohd. Asyraf Mansor, and Ahmad Izani Md Ismail, and Siti Zulaikha Mohd Jamaludin, and Mohd Shareduwan Mohd Kasihmuddin, and Mustafa Mamat, (2020) Novel random k Satisfiability for k ≤ 2 in hopfield neural network. Sains Malaysiana, 49 (11). pp. 2847-2857. ISSN 0126-6039 https://www.ukm.my/jsm/malay_journals/jilid49bil11_2020/KandunganJilid49Bil11_2020.html
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description The k Satisfiability logic representation (kSAT) contains valuable information that can be represented in terms of variables. This paper investigates the use of a particular non-systematic logical rule namely Random k Satisfiability (RANkSAT). RANkSAT contains a series of satisfiable clauses but the structure of the formula is determined randomly by the user. In the present study, RANkSAT representation is successfully implemented in Hopfield Neural Network (HNN) by obtaining the optimal synaptic weights. We focus on the different regimes for k ≤ 2 by taking advantage of the non-redundant logical structure, thus obtaining the final neuron state that minimizes the cost function. We also simulate the performances of RANkSAT logical rule using several performance metrics. The simulated results suggest that the RANkSAT representation can be embedded optimally in HNN and that the proposed method can retrieve the optimal final state.
format Article
author Saratha Sathasivam,
Mohd. Asyraf Mansor,
Ahmad Izani Md Ismail,
Siti Zulaikha Mohd Jamaludin,
Mohd Shareduwan Mohd Kasihmuddin,
Mustafa Mamat,
spellingShingle Saratha Sathasivam,
Mohd. Asyraf Mansor,
Ahmad Izani Md Ismail,
Siti Zulaikha Mohd Jamaludin,
Mohd Shareduwan Mohd Kasihmuddin,
Mustafa Mamat,
Novel random k Satisfiability for k ≤ 2 in hopfield neural network
author_facet Saratha Sathasivam,
Mohd. Asyraf Mansor,
Ahmad Izani Md Ismail,
Siti Zulaikha Mohd Jamaludin,
Mohd Shareduwan Mohd Kasihmuddin,
Mustafa Mamat,
author_sort Saratha Sathasivam,
title Novel random k Satisfiability for k ≤ 2 in hopfield neural network
title_short Novel random k Satisfiability for k ≤ 2 in hopfield neural network
title_full Novel random k Satisfiability for k ≤ 2 in hopfield neural network
title_fullStr Novel random k Satisfiability for k ≤ 2 in hopfield neural network
title_full_unstemmed Novel random k Satisfiability for k ≤ 2 in hopfield neural network
title_sort novel random k satisfiability for k ≤ 2 in hopfield neural network
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2020
url http://journalarticle.ukm.my/16014/1/23.pdf
http://journalarticle.ukm.my/16014/
https://www.ukm.my/jsm/malay_journals/jilid49bil11_2020/KandunganJilid49Bil11_2020.html
_version_ 1687394682985775104
score 13.251813

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