Demo Data from EDBT 2026 / reviewers in the wild / expert
William K. Pehlert
dblp:62/940
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 1986
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-authorTheory of computation · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Coding theory · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory
channel coding |
0.0 | 1 | 1973 | Correction of errors in multilevel Gray coded data · IEEE Trans. Inf. Theory 1973 |
Coding theory › error-correcting codes
coded modulation |
0.0 | 1 | 1973 | Correction of errors in multilevel Gray coded data · IEEE Trans. Inf. Theory 1973 |
Coding theory
error-correcting codes |
0.0 | 1 | 1973 | Correction of errors in multilevel Gray coded data · IEEE Trans. Inf. Theory 1973 |
Coding theory › error-correcting codes › combinatorial coding theory
gray codes |
0.0 | 1 | 1973 | Correction of errors in multilevel Gray coded data · IEEE Trans. Inf. Theory 1973 |
Coding theory › error-correcting codes › q-ary codes
nonbinary codes |
0.0 | 1 | 1973 | Correction of errors in multilevel Gray coded data · IEEE Trans. Inf. Theory 1973 |
Methods — techniques the papers use, named apart from their topics
soft-decision decoding · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1986 | Maintenance of the ACCUNET (R) Packet Service Network
William K. Pehlert, K. E. Carmichael, Mehmet Ulema |
ICC | 1 |
| 1973 | Correction of errors in multilevel Gray coded dataabstractIn this paper we present a new error-control technique intended for use in2^l-level data-transmission systems that employ Gray coding to transform a binary source sequence into the2^l-ary transmitted sequence. The codes, which we calli-compressed codes, make use of the structure of binary codes and have the property that for some integeri,1 \leq i \leq l, transmission errors can be corrected if the erroneously received signals lie less than2^{i-1}levels from the corresponding correct, or nominal signal levels. The number of such errors that can be corrected is related to the error-correcting capability of the underlying binary code used in the construction. In return for this restriction on the magnitude of correctable errors in the received signal, these codes have higher rates than binary codes of comparable length (in bits) and number of correctable errors. Hence in applications where it can be assumed that the fraction of errors exceeding a certain magnitude is negligible (or at least tolerable), this technique is more efficient than the conventional practice of placing a binary encoder between the data source and modulator and a binary decoder between the demodulator and data sink. Furthermore, although thei-compressed codes are nonbinary, the decoding algorithm is that of the underlying binary code plus a small amount of additional processing; hence it is generally simpler to implement than other nonbinary decoding algorithms. It is also observed that the rate of ani-compressed code is always greater than that of the underlying binary code. Thus certain classes of low-rate binary codes that have simple decoding algorithms can be used as underlying codes in the construction of high-rate easily decodablei-compressed codes. Finally, for the casei = 1, encoding and decoding becomes exceptionally simple and for this case it is possible to make use of "soft decisions" at the receiver to improve the performance. Paul Mecklenburg, William K. Pehlert, Daniel D. Sullivan |
IEEE Trans. Inf. Theory | 2 |