Demo Data from EDBT 2026 / reviewers in the wild / expert
L. L. McPheters
dblp:23/10899
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 100% | |
| Theoretical computer science
1 paper |
Coding theory · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems › data representation › data encoding › error correction coding
LDPC codes |
0.0 | 1 | 2001 | Iterative decoding for partial response (PR), equalized, magneto-optical (MO) data storage channels · IEEE J. Sel. Areas Commun. 2001 |
Storage systems › networked storage › storage networking
storage channels |
0.0 | 1 | 2001 | Iterative decoding for partial response (PR), equalized, magneto-optical (MO) data storage channels · IEEE J. Sel. Areas Commun. 2001 |
Coding theory
error-correcting codes |
0.0 | 1 | 2001 | Iterative decoding for partial response (PR), equalized, magneto-optical (MO) data storage channels · IEEE J. Sel. Areas Commun. 2001 |
Coding theory › error-correcting codes › decoding
iterative decoding |
0.0 | 1 | 2001 | Iterative decoding for partial response (PR), equalized, magneto-optical (MO) data storage channels · IEEE J. Sel. Areas Commun. 2001 |
Methods — techniques the papers use, named apart from their topics
turbo decoding · 0.1partial response maximum likelihood · 0.1LDPC decoding · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Iterative decoding for partial response (PR), equalized, magneto-optical (MO) data storage channelsabstractTurbo codes and low-density parity check (LDPC) codes with iterative decoding have received significant research attention because of their remarkable near-capacity performance for additive white Gaussian noise (AWGN) channels. Previously, turbo code and LDPC code variants are being investigated as potential candidates for high-density magnetic recording channels suffering from low signal-to-noise ratios (SNR). We address the application of turbo codes and LDPC codes to magneto-optical (MO) recording channels. Our results focus on a variety of practical MO storage channel aspects, including storage density, partial response targets, the type of precoder used, and mark edge jitter. Instead of focusing just on bit error rates (BER), we also study the block error statistics. Our results for MO storage channels indicate that turbo codes of rate 16/17 can achieve coding gains of 3-5 dB over partial response maximum likelihood (PRML) methods for a 10/sup -4/ target BER. Simulations also show that the performance of LDPC codes for MO channels is comparable to that of turbo codes, while requiring less computational complexity. Both LDPC codes and turbo codes with iterative decoding are seen to be robust to mark edge jitter. B. V. K. Vijaya Kumar, Erozan M. Kurtas, L. L. McPheters, Steven W. McLaughlin |
IEEE J. Sel. Areas Commun. | 5 |