2017
DOI: 10.1080/1206212x.2017.1396424
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Performance analysis of HFDI computing algorithm in intelligent networks

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Cited by 13 publications
(4 citation statements)
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“…The 4-bit CSA is proven for less power with help of FinFET (Ravi Sankar et al, 2018). Inexact registering (Mazahir et al, 2019) has presented new roads of equipment advancements in advanced plans for computationally broad applications, which can bear bargaining the precision in the conventional math as a compromise for improved force, speed or territory (Budati and Polipalli, 2019;Kumar and Rao, 2019). IJIUS 10,1 3.…”
Section: Introductionmentioning
confidence: 99%
“…The 4-bit CSA is proven for less power with help of FinFET (Ravi Sankar et al, 2018). Inexact registering (Mazahir et al, 2019) has presented new roads of equipment advancements in advanced plans for computationally broad applications, which can bear bargaining the precision in the conventional math as a compromise for improved force, speed or territory (Budati and Polipalli, 2019;Kumar and Rao, 2019). IJIUS 10,1 3.…”
Section: Introductionmentioning
confidence: 99%
“…The existing DA-based reconfigurable FIR filter yet to optimize the complexity in terms of adder delays and memory complexity are directly effecting on area, power and speed (Park and Meher, 2014;Budati and Polipalli, 2019). To address the issues discussed in literature, the proposed reconfigurable DA-based FIR with less number of LUTs has three fold advantages related to hardware structure, and those advantages are as follows: 1 For better sampling frequency, the number of taps is adjusted, and sampling rate is dependent of technology, which is required to adjust as per the block length.…”
Section: Proposed Methodology For Power Optimization Of Finite Impulse Responsementioning
confidence: 99%
“…The boundary error which is mean distance between the boundary of the obtained results and ground truth images were more consistently less is compared to semi-automated human annotator. Zilly et al (2017), Budati and Polipalli (2019) method is an improved version of two-way multi scale convolutional neural network with boosting approach. The simulation experiment has been performed using Drishti-GS and RIM-ONE database for performance analysis.…”
Section: Related Workmentioning
confidence: 99%