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<Article>
<Journal>
				<PublisherName>Semnan University</PublisherName>
				<JournalTitle>International Journal of Nonlinear Analysis and Applications</JournalTitle>
				<Issn>2008-6822</Issn>
				<Volume>6</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>11</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Probabilistic analysis of the asymmetric digital search trees</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>161</FirstPage>
			<LastPage>173</LastPage>
			<ELocationID EIdType="pii">266</ELocationID>
			
<ELocationID EIdType="doi">10.22075/ijnaa.2015.266</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Ramin</FirstName>
					<LastName>Kazemi</LastName>
<Affiliation>Department of Statistics,
 Imam Khomeini International University, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Qasem</FirstName>
					<LastName>Vahidi-asl</LastName>
<Affiliation>Department of Statistics,
 Shahid Beheshti University,
Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>06</Month>
					<Day>24</Day>
				</PubDate>
			</History>
		<Abstract>In this paper, by applying three functional operators the previous results on the (Poisson) variance of the external profile in digital search trees will be improved. We study the profile built over $n$ binary strings generated by a memoryless source with unequal probabilities of symbols and use a combinatorial approach for studying the Poissonized variance, since the probability distribution of the profile is unknown.</Abstract>
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			<Param Name="value">Digital search tree</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">profile</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">functional operators</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Poisson variance</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ijnaa.semnan.ac.ir/article_266_11e8d7699d96813d58500f0aaf6c6fbf.pdf</ArchiveCopySource>
</Article>
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