2002
DOI: 10.1109/18.971760
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On multiple insertion/deletion correcting codes

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Cited by 144 publications
(69 citation statements)
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“…At receiver, we can recover f (x 7 ) as g(x 7 ) ∈ C 2 (6). Furthermore, we know that the symbols 2 and 1 were deleted due to the constraints in (5). However, we do not know which symbol came first in the original codeword x 7 .…”
Section: Ieee Information Theory Workhopmentioning
confidence: 93%
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“…At receiver, we can recover f (x 7 ) as g(x 7 ) ∈ C 2 (6). Furthermore, we know that the symbols 2 and 1 were deleted due to the constraints in (5). However, we do not know which symbol came first in the original codeword x 7 .…”
Section: Ieee Information Theory Workhopmentioning
confidence: 93%
“…Our construction is based on any [2] Tenengol'ts [4] Multiple Ins./Del. Correction Helberg [5] Proposed Construction Method (This Paper) binary multiple insertion/deletion correcting code, such as the Helberg code. Table I places our construction in context in comparison to other insertion/deletion correcting codes.…”
Section: Introductionmentioning
confidence: 99%
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“…However, this code is inefficient because it requires δn redundant bits, i.e., a redundancy that is linear in n. Helberg codes [12] are a generalization of VT codes for multiple deletions. These codes can correct mutiple deletions but their redundancy is at least linear in n even for two deletions.…”
Section: Introductionmentioning
confidence: 99%
“…Contributions: While the work on codes that correct multiple deletions in [12]- [15] focuses on zero-error codes, in our approach we relax this requirement and allow an asymptotically vanishing probability of decoding failure 1 . Our contributions are the following: (i) we propose new explicit codes, which we call Guess & Check (GC) codes, that can correct, with high probability, and in polynomial time, a constant number of deletions 2 δ occurring at uniformly random positions within an arbitrary binary string.…”
Section: Introductionmentioning
confidence: 99%