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<Article>
<Journal>
				<PublisherName>University of Kashan</PublisherName>
				<JournalTitle>Soft Computing Journal</JournalTitle>
				<Issn>2322-3707</Issn>
				<Volume>1</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2021</Year>
					<Month>05</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A Review of Quantum Neural Networks</ArticleTitle>
<VernacularTitle>A Review of Quantum Neural Networks</VernacularTitle>
			<FirstPage>46</FirstPage>
			<LastPage>55</LastPage>
			<ELocationID EIdType="pii">111356</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Khosravi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Maryam</FirstName>
					<LastName>Zekri</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>05</Month>
					<Day>23</Day>
				</PubDate>
			</History>
		<Abstract>In this paper the development of quantum neural networks (QNN), and some of presented models and physical implementation are reviewed. How of making use of double-slit experiment for implementing QNN and methods of designing as well as examples of two-layer hybrid networks in QNN constructed from quantum neurons and classical neurons are represented. Some application models of the networks (QNN) is compared with classical models and capabilities of QNN together with the quantum mechanical concepts in solving difficult  problems, which is hard to solve by classical models, is noted.</Abstract>
			<OtherAbstract Language="FA">In this paper the development of quantum neural networks (QNN), and some of presented models and physical implementation are reviewed. How of making use of double-slit experiment for implementing QNN and methods of designing as well as examples of two-layer hybrid networks in QNN constructed from quantum neurons and classical neurons are represented. Some application models of the networks (QNN) is compared with classical models and capabilities of QNN together with the quantum mechanical concepts in solving difficult  problems, which is hard to solve by classical models, is noted.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">quantum neural network</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">quantum computing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">two-layer hybrid network</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">quantum neurons</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">quantum information processing</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://scj.kashanu.ac.ir/article_111356_3a74a34fd73f21730abe1942869c7580.pdf</ArchiveCopySource>
</Article>
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