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<Article>
<Journal>
				<PublisherName>Semnan University</PublisherName>
				<JournalTitle>International Journal of Nonlinear Analysis and Applications</JournalTitle>
				<Issn>2008-6822</Issn>
				<Volume>12</Volume>
				<Issue>Special Issue</Issue>
				<PubDate PubStatus="epublish">
					<Year>2021</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Design and implementation of low complexity LMS adaptive filter</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>1827</FirstPage>
			<LastPage>1833</LastPage>
			<ELocationID EIdType="pii">5893</ELocationID>
			
<ELocationID EIdType="doi">10.22075/ijnaa.2021.5893</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>V.</FirstName>
					<LastName>Chowthri</LastName>
<Affiliation>ME VLSI, ECE, PSG College of Technology, India</Affiliation>

</Author>
<Author>
					<FirstName>A.</FirstName>
					<LastName>Uma</LastName>
<Affiliation>Department of ECE, PSG College of Technology Coimbatore, India</Affiliation>

</Author>
<Author>
					<FirstName>P.</FirstName>
					<LastName>Kalpana</LastName>
<Affiliation>Department of ECE,PSG College of Technology, India</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2021</Year>
					<Month>08</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		<Abstract>An adaptive filter is a real-time computational device that iteratively simulates the relationship between a filter&#039;s input and output signals. It is based on an adaptive algorithm that iteratively self-adjusts the linear filter coefficients to decrease the power of e. (n). The LMS method is one of the most widely used adaptive algorithms for adjusting the coefficients of adaptive filters, among others. The error-computation block and the weight-update block, which determine the filter&#039;s efficiency, are the two key computing blocks of the direct-form LMS adaptive filter. In this paper, adaptive filter is implemented in two different architectures namely, zero adaptation delay adaptive filter and two adaptations delay adaptive filter which results in low power consumption and less area complexity. Zero adaptation delay adaptive filter provides nearly 52\% savings in the area and the delay decreases by 26\% in two adaptations delay adaptive filter over the conventional adaptive filter. Hence based on the required speed and area for the application, any one of the proposed structures can be used.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Adaptive filter</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Least mean square algorithms</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">LMS adaptive filter</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Adaptation delay</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Area</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">delay</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://ijnaa.semnan.ac.ir/article_5893_d84d87029c3a34cee5a8998797243067.pdf</ArchiveCopySource>
</Article>
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