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Neurocomputing, 2020
Convolutional neural networks (CNNs) represent deep learning architectures that are currently used in a wide range of applications, including computer vision, speech recognition, time series analysis in finance, and many others.
N. Chervyakov +5 more
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Convolutional neural networks (CNNs) represent deep learning architectures that are currently used in a wide range of applications, including computer vision, speech recognition, time series analysis in finance, and many others.
N. Chervyakov +5 more
semanticscholar +1 more source
Perspective and Opportunities of Modulo 2n-1 Multipliers in Residue Number System: A Review
J. Circuits Syst. Comput., 2020Modulo multiplier has been attracting considerable attention as one of the essential components of residue number system (RNS)-based computational circuits.
Raj Kumar, R. Jaiswal, R. Mishra
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Steganography over Redundant Residue Number System Codes
Journal of Information Security and Applications, 2020In this paper we define steganography over Redundant Residue Number System (RRNS) Codes. We describe distortion-less RRNS based steganographic schemes, analyse their corresponding embedding capacities, discuss their linearity and compare them with well ...
M. Belhamra, E. M. Souidi
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Error Control in Residue Number Systems
Applicable Algebra in Engineering, Communication and Computing, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Miller, David F., Rutter, Edgar A.
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Integer division in residue number systems
IEEE Transactions on Computers, 1995Summary: This contribution to the ongoing discussion of division algorithms for Residue Number Systems (RNS) is based on Newton iteration for computing the reciprocal. An extended RNS with twice the number of moduli provides the range required for multiplication and scaling. Separation of the algorithm description from its RNS implementation achieves a
Hitz, Markus A., Kaltofen, Erich
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Scaling in residue number systems
Cybernetics, 1990Let \(m_ 1,\dots,m_ k\) be pairwise relatively prime integers \((k \geq 2)\), with \(m_ 1m_ 2\dots m_ k = M\). It is desired to approximate \(A/S\) by modular arithmetic, where \(S\) is a positive rational number and \(A\) is an integer such that \(2| A| \leq M\). A method is given for doing this in a form suitable for parallel processing.
Vasilevich, L. N., Kolyada, A. A.
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IEEE transactions on circuits and systems for video technology (Print), 2019
A residue number system (RNS) has an inherent parallel structure that can be utilized for improving computer hardware systems. An RNS represents large integer numbers as a smaller integer set, or residues of a modulo set, without carry propagation ...
Niras C. Vayalil, M. Paul, Yinan Kong
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A residue number system (RNS) has an inherent parallel structure that can be utilized for improving computer hardware systems. An RNS represents large integer numbers as a smaller integer set, or residues of a modulo set, without carry propagation ...
Niras C. Vayalil, M. Paul, Yinan Kong
semanticscholar +1 more source
2014
Residue Number Systems have probed their potential for computation-intensive applications, especially those related to signal processing. Their main advantage is the absence of carry propagation between channels in addition, subtraction and multiplication.
Antonio Lloris Ruiz +3 more
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Residue Number Systems have probed their potential for computation-intensive applications, especially those related to signal processing. Their main advantage is the absence of carry propagation between channels in addition, subtraction and multiplication.
Antonio Lloris Ruiz +3 more
openaire +1 more source
RNSnet: In-Memory Neural Network Acceleration Using Residue Number System
International Conference on Rebooting Computing, 2018We live in a world where technological advances are continually creating more data than what we can deal with. Machine learning algorithms, in particular Deep Neural Networks (DNNs), are essential to process such large data.
Sahand Salamat +3 more
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