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Proceedings of the 26th Asia and South Pacific Design Automation Conference, 2021
In this paper, we present our state-of-the-art approximate techniques that cover the main pillars of approximate computing research. Our analysis considers both static and reconfigurable approximation techniques as well as operation-specific approximate components (e.g., multipliers) and generalized approximate high-level synthesis approaches.
Georgios Zervakis 0001 +5 more
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In this paper, we present our state-of-the-art approximate techniques that cover the main pillars of approximate computing research. Our analysis considers both static and reconfigurable approximation techniques as well as operation-specific approximate components (e.g., multipliers) and generalized approximate high-level synthesis approaches.
Georgios Zervakis 0001 +5 more
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MLS-based variable-node elements compatible with quadratic interpolation. Part I: formulation and application for non-matching meshes [PDF]
International Journal for Numerical Methods in Engineering, 2006 Two-dimensional variable-node elements compatible with quadratic interpolation are developed using the moving least-square (MLS) approximation.
Young-Sam Cho, Seyoung Im
exaly +2 more sources
Approximations to joint-ML and ML symbol-channel estimators in MUD CDMA
Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE, 2003In this contribution we conceptually derive two symbol-channel estimators, the joint-ML and the ML, both having exponential complexity. Pragmatically we derive three approximations with polynomial complexity, one to the joint-ML: the pseudo-joint-ML; two to the ML: the naive-ML and the linear-response-ML. We assess the resulting average bit error rates
Thomas Fabricius, Ole Nørklit
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A Novel Approximation of NDA ML Estimation for UWB Channels
IEEE Transactions on Communications, 2010Novel non-data-aided near-maximum-likelihood estimators for the delays and the attenuations in an ultra-wide bandwidth channel are proposed by using an approximation to the maximum likelihood equation. Numerical results show that these new estimators outperform previous approximate non-data-aided maximum likelihood channel estimators reported in the ...
Yunfei Chen 0001, Norman C. Beaulieu
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Design of Majority Logic (ML) Based Approximate Full Adders
2018 IEEE International Symposium on Circuits and Systems (ISCAS), 2018As a new paradigm in the nanoscale technologies, approximate computing enables error tolerance in the computational process; it has also emerged as a low power design methodology for arithmetic circuits. Majority logic (ML) is applicable to many emerging technologies and its basic building block (the 3-input majority voter) has been extensively used in
Tingting Zhang +4 more
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Approximate ML detection for MIMO systems with very low complexity
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004Recently many space-time coding schemes for multiple antenna systems (MIMO) have been proposed in order to achieve high data rates when transmitting over wireless channels. However, most of such schemes rely on maximum likelihood (ML) detection, which can become quite complex when many antennas are involved and higher modulation schemes are utilized ...
Markus Rupp +2 more
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Efficient approximate ML decoding units for polar list decoders
2015 IEEE Workshop on Signal Processing Systems (SiPS), 2015Polar codes are of great interest since they are the first provably capacity-achieving forward error correction codes. To improve throughput of polar decoders, maximum likelihood (ML) decoding units are used by successive cancellation list (SCL) decoders as well as successive cancellation (SC) decoders.
Chenrong Xiong +2 more
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A Smoothed GFEM Based on Taylor Expansion and Constrained MLS for Analysis of Reissner–Mindlin Plate
International Journal of Computational Methods, 2021Based on the Taylor Expansion and constrained moving least square function, a smoothed GFEM (SGFEM) is proposed in this paper for static, free vibration and buckling analysis of Reissner–Mindlin plate. The displacement function based on SGFEM is composed
Tang Jinsong +2 more
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Communications in nonlinear science & numerical simulation, 2020
The moving least-squares (MLS) approximation is a powerful numerical scheme widely used in the meshfree literature to construct local multivariate polynomial basis functions for expanding the solution of a given differential or integral equation.
M. Shirzadi, M. Dehghan, A. F. Bastani
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The moving least-squares (MLS) approximation is a powerful numerical scheme widely used in the meshfree literature to construct local multivariate polynomial basis functions for expanding the solution of a given differential or integral equation.
M. Shirzadi, M. Dehghan, A. F. Bastani
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Approximate ML-estimates of random processes
Proceedings of 1994 IEEE International Symposium on Information Theory, 2002Computationally feasible versions of maximum likelihood estimations (MLEs), called approximate MLEs (AMLEs), are introduced. Estimation models with all, some, or no AMLEs consistent are presented. >
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