2019
DOI: 10.1016/j.micpro.2019.102883
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Low power and low area VLSI implementation of vedic design FIR filter for ECG signal de-noising

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Cited by 43 publications
(28 citation statements)
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“…This described VD-CLA structure can improve by taking a gander at other electronic system performance metrics to seek the best arrangement of attributes intended for a specific denoising application, e.g., mean squared error (MSE), signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), bit error rate (BER), and [25,[36][37][38][39][40][41].…”
Section: Discussionmentioning
confidence: 99%
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“…This described VD-CLA structure can improve by taking a gander at other electronic system performance metrics to seek the best arrangement of attributes intended for a specific denoising application, e.g., mean squared error (MSE), signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), bit error rate (BER), and [25,[36][37][38][39][40][41].…”
Section: Discussionmentioning
confidence: 99%
“…Distributed arithmetic (DA) calculation employs a high request FIR channel FIRF is consolidated with a MAC unit to increase the contribution of coefficients, to move, and after that to include them. However, the delay augments Sumalatha et al [25] A low-power and low-area VLSI implementation of the VD FIRF for ECG signal denoising Low-power and fast FIRF implemented using Vedic multiplier and 16-bit CLA adder for ECG denoising application Doss et al [22] The pipelined architecture for adaptive FIRF design employed the DA algorithm with a highthroughput rate achieved by the updated LUT…”
Section: Literature Reviewmentioning
confidence: 99%
“…The estimated delay based on (Gate delay-DG) for Distributed Arithmetic unit of LUT, LUT-less and Int J Elec & Comp Eng ISSN: 2088-8708  Design and implementation of DA FIR filter for bio-inspired computing architecture (B. U. V. Prashanth)1715proposed architecture implementation[22,23] is as shown in the Figure8. Here the delay of the proposed architecture is 14 % (for 8-order filter) and 64.7% (for 140-order filter) less delay in comparison of LUT-less architecture[24,25].…”
mentioning
confidence: 87%
“…Pada artikel ini akan dikembangkan penggunakan filter IIR pada data sinyal pernapasan EMGdi pernah dilakukan pada [2] dengan membandingkan segi keefektifan filter dengan menggunakan filter FIR. Berdasarkan [3][4] filter FIR mampu menghilangkan noise pada pengaplikasian sinyal ECG karena memiliki properti fasa yang linear dan karakteristik yang stabil serta mampu meningkatkan kecepatan kalkulasi filter sebesar 13,65%. Oleh karena itu, artikel ini akan mencoba mengaplikasikan penelitian [2] dengan menggunakan filter FIR dan melihat apakah keefektifan filter tersebut juga berlaku ketika diaplikasikan pada sinyal EMGdi dengan menggunakan Signal-to-Noise Ratio (SNR), execution time, serta zero-pole diagram kedua filter.…”
Section: Pendahuluanunclassified