Decoding Real-Field Codes by an Iterative Expectation-Maximization (EM) Algorithm

Abstract : In this paper, a new approach for decoding real-field codes based on finding sparse solutions of underdetermined linear systems is proposed. This algorithm iteratively estimates the positions and the amplitudes of the sparse errors (or noise impulses using an Expectation-Maximization (EM) algorithm. Iterative estimation of amplitudes is done in the Expectation step (E-step), while iterative estimation of error positions is done in the Maximization step (M-step). Simulation results show 1-2 dB improvement over Linear Programming (LP) which has been previously used for error correction.
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Contributor : Christian Jutten <>
Submitted on : Tuesday, April 8, 2008 - 7:22:45 PM
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Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutten. Decoding Real-Field Codes by an Iterative Expectation-Maximization (EM) Algorithm. IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2008, Mar 2008, Las Vegas, United States. pp.3169-3172. ⟨hal-00271360⟩



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