Results 41 to 50 of about 4,791 (236)
Low Complexity Syndrome-Based Decoding Algorithm Applied to Block Turbo Codes
IEEE Access, 2018 This paper presents a technique for reducing the decoding complexity of block turbo code with an extended Hamming code as a component code. In conventional decoding algorithms, when an input vector has a zero syndrome, complexity can be reduced by using ...
Byungkyu Ahn, Sungsik Yoon, Jun Heo
doaj +1 more source
Inter-Block Permuted Turbo Codes
CoRR, 2006 44 pages, 17 ...
Yan-Xiu Zheng, Yu T. Su
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Network‐turbo‐coding‐based cooperation with distributed space‐time block codes [PDF]
Transactions on Emerging Telecommunications Technologies, 2014 AbstractIn this paper, we propose a scheme to improve the performance of turbo‐coded two‐user cooperative uplink transmission. In the proposed scheme, each user transmits its partner's second parity frame in addition to its own, using a network‐coded combination, which is further protected by a space‐time block code. The proposed system is simulated in
Bin Chen 0006, Mark F. Flanagan
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Time‐Conditioned Zero‐Shot Self‐Supervised Reconstruction for Accelerated 3D Ultra‐Low‐Field MRI
Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose Ultra‐low‐field (ULF) MRI provides a cost‐effective, portable imaging option but has relatively low SNR and long acquisition times compared to standard clinical scans. This study presents a time‐conditioned zero‐shot self‐supervised learning image reconstruction framework (ULF‐ZS‐SSL) to accelerate 3D‐acquired single‐coil ULF MRI ...
Mart W. J. van Straten +6 more
wiley +1 more source
Comparative study of turbo equalisers using convolutional codes and block-based turbo codes for GMSK modulation [PDF]
Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No.99CH36324), 2003 In contrast to previously proposed turbo equalisers, where typically non-iterative channel decoders were used, this paper compares the performance of partial-response GMSK turbo equalisers using two different encoders, namely block BCH turbo codes and convolutional codes.
Yeap, B.L. +3 more
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Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose The Unadjusted Langevin Algorithm (ULA) in combination with diffusion models can generate high quality MRI reconstructions with uncertainty estimation from highly undersampled k‐space data. However, sampling methods such as diffusion posterior sampling (DPS) or likelihood annealing suffer from long reconstruction times and the need for
Moritz Blumenthal +3 more
wiley +1 more source
Magnetic Resonance in Medicine, EarlyView.ABSTRACT Purpose Segmented 3D Gradient and Spin Echo (GRASE) is commonly used in Arterial Spin Labeling (ASL) perfusion imaging. However, it is vulnerable to inter‐shot motion, leading to subtraction errors that cannot be corrected. We developed a retrospective self‐navigated inter‐shot motion correction method for segmented 3D‐GRASE ASL imaging with ...
Minhao Hu +5 more
wiley +1 more source
Combined Distributed Turbo Coding and Space Frequency Block Coding Techniques
EURASIP Journal on Wireless Communications and Networking, 2010 The distributed space-time (frequency) coding and distributed channel turbo coding used independently represent two cooperative techniques that can provide increased throughput and spectral efficiency at an imposed maximum Bit Error Rate (BER) and delay required from the new generation of cellular networks.
Vasile Bota +7 more
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Performance of Reed-Solomon block turbo code [PDF]
Proceedings of GLOBECOM'96. 1996 IEEE Global Telecommunications Conference, 2002 Thanks to recent progress in the iterative decoding of concatenated codes, several new fields of investigation have appeared. In this paper, we present a first approach of the iterative decoding of Reed-Solomon (RS) product codes: "Turbo codes RS". Two methods to construct RS product codes are given.
O. Aitsab, R. Pyndiah
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Magnetic Resonance in Medicine, EarlyView.ABSTRACT Aims Purpose: Dictionary matching is a standard tool in quantitative MRI (qMRI), but typically lacks uncertainty quantification (UQ). This is critical when advanced reconstructions (e.g., compressed sensing, deep learning) introduce complex‐valued, spatially varying, and temporally correlated noise that violates standard assumptions of ...
Brian Toner +7 more
wiley +1 more source