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The application of interpolating MLS approximations to the analysis of MHD flows
Finite Elements in Analysis and Design, 2003The element-free Galerkin method (EFGM) is a very attractive technique for solutions of partial differential equations, since it makes use of nodal point configurations which do not require a mesh. Therefore, it differs from FEM-like approaches by avoiding the need of meshing, a very demanding task for complicated geometry problems.
Verardi, SLL, Machado, J. M., Shiyou, Y.
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Approximate ber expression of ML equalizer for OFDM over doubly selective channels
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008Maximum Likelihood (ML) equalization for Orthogonal Frequency Division Multiplexing (OFDM) over time- and frequency- selective channels is analyzed in this paper. An approximate expression for bit error rate (BER) performance of the ML equalizer with a limited number of taps is developed, which subsumes the matched filter bound (MFB) equalization ...
null Shuichi Ohno +1 more
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Approximate ML decoding of coded PSK with no explicit carrier phase reference
IEEE Transactions on Communications, 1994An approximate method is discussed for maximum likelihood estimation of coded PSK sequences in the presence of an unknown carrier phase. This method makes use of the Viterbi algorithm to find an optimum path in the encoder trellis diagram. Phase estimation is embedded into the structure of the detection algorithm and the branch metrics in the trellis ...
A. N. D'ANDREA +2 more
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Efficient construction of approximate ad-hoc ML models through materialization and reuse
Proceedings of the VLDB Endowment, 2018Machine learning has become an essential toolkit for complex analytic processing. Data is typically stored in large data warehouses with multiple dimension hierarchies. Often, data used for building an ML model are aligned on OLAP hierarchies such as location or time.
Sona Hasani +4 more
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Blended Hermite MLS Approximation for Discretizing Biharmonic Parial Differential Equations
2008Meshless methods are an appealing choice for constructing functional approximations (with different degrees of consistency and continuity) without a mesh support. Some members of the vast family of meshless methods are the smooth particle hydrodynamics (SPH) proposed in , the element free Galekin (EFG) , the diffuse elements (DE) , the reproducing ...
Joyot, Pierre +3 more
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Applications of the Approximate Computing on ML Architecture
2021Kattekola Naresh, Shubhankar Majumdar
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ML-PLAC: Multiplierless Piecewise Linear Approximation for Nonlinear Function Evaluation
IEEE Transactions on Circuits and Systems I: Regular Papers, 2022Fei Lyu +5 more
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Energy-Efficient Approximate Multipliers for ML-Based Disease Detection Systems
2022Zainab Aizaz, Kavita Khare
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Achievability Approximation of IDS Hub Using Collaborative Network Model With ML
2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT), 2023Nitish Kumar Ojha +3 more
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