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<records>

  <record>
    <language>eng</language>
          <publisher>Oriental Scientific Publishing Company</publisher>
        <journalTitle>Biomedical and Pharmacology Journal</journalTitle>
          <issn>0974-6242</issn>
            <publicationDate>2020-03-28</publicationDate>
    
        <volume>13</volume>
        <issue>1</issue>

 
    <startPage>19</startPage>
    <endPage>25</endPage>

	 
      <doi> 10.13005/bpj/1855</doi>
        <publisherRecordId>30439</publisherRecordId>
    <documentType>article</documentType>
    <title language="eng">A Novel Approach of QMF Bank using Modified PSO Technique for Biomedical Image Applications</title>

    <authors>
	 


      <author>
       <name>Bhumika Gupta</name>

 
		
	<affiliationId>1</affiliationId>
      </author>
    

	 


      <author>
       <name>Agya Ram Verma</name>


		
	<affiliationId>2</affiliationId>

      </author>
    

	 


      <author>
       <name>Manoj Kumar</name>

		
	<affiliationId>2</affiliationId>
      </author>
    

	


	


	
    </authors>
    
	    <affiliationsList>
	    
		
		<affiliationName affiliationId="1">Department of Computer Science Engineering G.B.Pant Institute of Engineering and Technology, India </affiliationName>
    

		
		<affiliationName affiliationId="2">Department of Electronic and Communication Engineering G.B.Pant Institute of Engineering and Technology, India</affiliationName>
    
		
		
		
		
	  </affiliationsList>






    <abstract language="eng">In this paper, we propose the design of the Quadrature Mirror Filter (QMF) two-channel linear phase bank with modified particle swarm optimization (MPSO) algorithm. Traditional other reported methods for QMF bank design, were compared to the performance of proposed scheme. Based on simulation results, it is shown that the stated method can achieve 26%, 83%, 97%, 84% as well as 67%, respectively reduction in amplitude, transfer band, impede band, alteration band, with peak reconstruction errors. In comparison, the proposed QMF bank applied for biomedical image reconstruction shows 2.2 folds reduction in mean square error with an improvement of 5 dB in peak signal-to-noise ratio as compared to recently reported Levenberga algorithm.</abstract>

    <fullTextUrl format="html">https://biomedpharmajournal.org/vol13no1/a-novel-approach-of-qmf-bank-using-modified-pso-technique-for-biomedical-image-applications/</fullTextUrl>

<keywords language="eng">

      
        <keyword>Biomedical Image</keyword>
      

      
        <keyword> MPSO</keyword>
      

      
        <keyword> Sub-Band Coding</keyword>
      

      
        <keyword> PSO</keyword>
      

      
        <keyword> QMF</keyword>
      
</keywords>
  </record>
</records>