2019
DOI: 10.1109/tvlsi.2018.2883645
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A Two-Speed, Radix-4, Serial–Parallel Multiplier

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Cited by 44 publications
(5 citation statements)
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“…To address these constraints, this study devised a stress classification technique that utilizes the multi-dimensional feature fusion of LSTM and Xception. Further, to address the problem of morphological damages in ECG caused by motion artifacts, which can reduce the effectiveness of the proposed technique, outlier signals were eliminated from the ECG data [19]. A power-efficient FFT processor is designed for embedded DSP systems, focusing on variable-length processing.…”
Section: Literature Reviewmentioning
confidence: 99%
“…To address these constraints, this study devised a stress classification technique that utilizes the multi-dimensional feature fusion of LSTM and Xception. Further, to address the problem of morphological damages in ECG caused by motion artifacts, which can reduce the effectiveness of the proposed technique, outlier signals were eliminated from the ECG data [19]. A power-efficient FFT processor is designed for embedded DSP systems, focusing on variable-length processing.…”
Section: Literature Reviewmentioning
confidence: 99%
“…A modified Radix-4 Booth multiplier that only adds non-zero Booth encodings and disregards zero operations 18 . To do the hard multiple 3X operations, use 3X = 2X + X 19 .…”
Section: Related Workmentioning
confidence: 99%
“…Radix-4, serial -parallel multiplier is designed by Moss et al (2018) for improving the performance of different applications like filtering, machine learning and neural network-based systems [30]. This multiplier is realized by Intel Cyclone V FPGA for 32-bit and 64-bit operations.…”
Section: Liu Et Al 2016 Designed An Approximate Radix-4 Boothmentioning
confidence: 99%
“…Both ABM and STBMBM [23] are used for finite impulse responnse (FIR) filter. SPM [30] is used for implementing filter as well as meachine learning (ML) algorithms. DABMAU [27] is applied for desigining discrete wavelet transform (DWT) and B2CBBM [29] is suitable for implementing graphical processor units (GPU).…”
Section: Comparative Analysismentioning
confidence: 99%