Rns System With Improved Reverse Conversion Process For High Performance Dsp Applications.

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Title: Rns System With Improved Reverse Conversion Process For High Performance Dsp Applications.
Authors: Kumar, T. R. Dinesh1, Bennet, M. Anto2 drmantobenet@veltech.edu.in, Sowmiya, R.3, Saranya, S.3, Yuvasree, R.3
Source: Turkish Online Journal of Qualitative Inquiry. 2021, Vol. 12 Issue 5, p4397-4404. 8p.
Subject Terms: Nurses, Digital signal processing, Modular arithmetic, Noise control
Abstract: Digital filtering is the core of digital signal processing, since it underlies the solution of most practical problems in this area: noise reduction, amplification and suppression of frequencies, interpolation, decimation, equalization and many others. In recent years DSP applications deals with samples of high bit sizes for improved precisions which required large amount of hardware resources for computation. Irrespective of arithmetic models used for data computation the tradeoff is always exists with word length size. To retain the performance metrics in terms of speed it is essential to invent some mathematics based on modular fields for arithmetic computations. In addition to that, this work also proposes a decomposed LUT based residuegeneration for RNS MACcore that constitutes simpler arithmetic operation which explores improved path delay optimization level. It is proved that inRNS as compared all other functions reverse conversion process is directly influence the overall RNS system performance both in terms of power consumption overhead, performance measures and path delay etc. Here reverse conversion can be implemented using decomposed LUTwhich produces high performance FIR design. [ABSTRACT FROM AUTHOR]
Copyright of Turkish Online Journal of Qualitative Inquiry is the property of Turkish Online Journal of Qualitative Inquiry and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Rns System With Improved Reverse Conversion Process For High Performance Dsp Applications.
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  Data: <searchLink fieldCode="AR" term="%22Kumar%2C+T%2E+R%2E+Dinesh%22">Kumar, T. R. Dinesh</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Bennet%2C+M%2E+Anto%22">Bennet, M. Anto</searchLink><relatesTo>2</relatesTo><i> drmantobenet@veltech.edu.in</i><br /><searchLink fieldCode="AR" term="%22Sowmiya%2C+R%2E%22">Sowmiya, R.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Saranya%2C+S%2E%22">Saranya, S.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Yuvasree%2C+R%2E%22">Yuvasree, R.</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Turkish+Online+Journal+of+Qualitative+Inquiry%22">Turkish Online Journal of Qualitative Inquiry</searchLink>. 2021, Vol. 12 Issue 5, p4397-4404. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Nurses%22">Nurses</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+signal+processing%22">Digital signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Modular+arithmetic%22">Modular arithmetic</searchLink><br /><searchLink fieldCode="DE" term="%22Noise+control%22">Noise control</searchLink>
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  Label: Abstract
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  Data: Digital filtering is the core of digital signal processing, since it underlies the solution of most practical problems in this area: noise reduction, amplification and suppression of frequencies, interpolation, decimation, equalization and many others. In recent years DSP applications deals with samples of high bit sizes for improved precisions which required large amount of hardware resources for computation. Irrespective of arithmetic models used for data computation the tradeoff is always exists with word length size. To retain the performance metrics in terms of speed it is essential to invent some mathematics based on modular fields for arithmetic computations. In addition to that, this work also proposes a decomposed LUT based residuegeneration for RNS MACcore that constitutes simpler arithmetic operation which explores improved path delay optimization level. It is proved that inRNS as compared all other functions reverse conversion process is directly influence the overall RNS system performance both in terms of power consumption overhead, performance measures and path delay etc. Here reverse conversion can be implemented using decomposed LUTwhich produces high performance FIR design. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Turkish Online Journal of Qualitative Inquiry is the property of Turkish Online Journal of Qualitative Inquiry and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Code: eng
        Text: English
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        PageCount: 8
        StartPage: 4397
    Subjects:
      – SubjectFull: Nurses
        Type: general
      – SubjectFull: Digital signal processing
        Type: general
      – SubjectFull: Modular arithmetic
        Type: general
      – SubjectFull: Noise control
        Type: general
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      – TitleFull: Rns System With Improved Reverse Conversion Process For High Performance Dsp Applications.
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            NameFull: Bennet, M. Anto
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            NameFull: Sowmiya, R.
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            NameFull: Saranya, S.
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            NameFull: Yuvasree, R.
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            – D: 01
              M: 06
              Text: 2021
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              Y: 2021
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