2023
DOI: 10.1002/cpe.7629
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Design of recustomize finite impulse response filter using truncation based scalable rounding approximate multiplier and error reduced carry prediction approximate adder for image processing application

Abstract: Summary Recustomize finite impulse response (RFIR) filter is designed to achieve lesser power consume, cost, area, and higher speed of system operation. This is used to remove the noises from the image and signal. Previously, several filters were designed for removing noises, but that filters consume more area, power, cost, and delay and did not provide accurate results and the error rate was increased. To overcome these issues, this work is proposed. In this work, the Recustomize finite impulse response (RFIR… Show more

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Cited by 16 publications
(2 citation statements)
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“…Acc is the proportion of correctly classified samples over the total number of samples in the dataset, as in (5). F1 score evaluates the harmonic mean of precision and recall, as in (8). It offers a balanced evaluation of model performance by incorporating both precision and recall.…”
Section: B Performance Evaluationmentioning
confidence: 99%
“…Acc is the proportion of correctly classified samples over the total number of samples in the dataset, as in (5). F1 score evaluates the harmonic mean of precision and recall, as in (8). It offers a balanced evaluation of model performance by incorporating both precision and recall.…”
Section: B Performance Evaluationmentioning
confidence: 99%
“…In [20], the authors analyzed the performance of the three pilot-aided algorithms, namely the RLS, LMS, and ZF, for a generalized multi-path communication channel. This paper analyses least mean squares (LMS) linear, LMS Decision feedback equalizer (DFE) [21], Recursive Least Squares (RLS) linear, RLS-DFE algorithms that requires a reference signal [22].…”
Section: Introductionmentioning
confidence: 99%