TY - GEN
T1 - How to Find Simple Conditions for Successful Sequence Reconstruction?
AU - Wang, Chen
AU - Yaakobi, Eitan
AU - Zhang, Yiwei
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - We study a model in which a codeword x is transmitted through several identical channels, where each channel produces a noisy read of x. The sequence reconstruction problem, proposed by Levenshtein, asks for how to uniquely re-construct x based on these noisy reads. Most of previous works focused on the minimum number of reads which guarantees unique reconstruction of x in the worst case. In this paper, we move on to a new perspective on the sequence reconstruction problem, and propose a different sufficient condition for unique reconstruction which takes both the number of reads and the distances among the reads into consideration. We offer both theoretical analysis and corresponding efficient reconstruction algorithms.
AB - We study a model in which a codeword x is transmitted through several identical channels, where each channel produces a noisy read of x. The sequence reconstruction problem, proposed by Levenshtein, asks for how to uniquely re-construct x based on these noisy reads. Most of previous works focused on the minimum number of reads which guarantees unique reconstruction of x in the worst case. In this paper, we move on to a new perspective on the sequence reconstruction problem, and propose a different sufficient condition for unique reconstruction which takes both the number of reads and the distances among the reads into consideration. We offer both theoretical analysis and corresponding efficient reconstruction algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85216550253&partnerID=8YFLogxK
U2 - 10.1109/ITW61385.2024.10807014
DO - 10.1109/ITW61385.2024.10807014
M3 - منشور من مؤتمر
T3 - 2024 IEEE Information Theory Workshop, ITW 2024
SP - 627
EP - 632
BT - 2024 IEEE Information Theory Workshop, ITW 2024
T2 - 2024 IEEE Information Theory Workshop, ITW 2024
Y2 - 24 November 2024 through 28 November 2024
ER -