Demo Data from EDBT 2026 / reviewers in the wild / expert
D. Murthy
dblp:10/664
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 1988
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 first-authorTheory of computation · 1 · 1 first-author
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 |
Information theory · 50% Mathematical optimization · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization › dynamical systems
discrete-time systems |
0.0 | 1 | 1973 | Factorization of discrete-process spectral matrices (Corresp.) · IEEE Trans. Inf. Theory 1973 |
Information theory › signal processing
spectral factorization |
0.0 | 1 | 1973 | Factorization of discrete-process spectral matrices (Corresp.) · IEEE Trans. Inf. Theory 1973 |
Methods — techniques the papers use, named apart from their topics
matrix factorization · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1988 | Split sequence coalesced hashing
D. Murthy, Pradip K. Srimani |
Inf. Syst. | 1 |
| 1973 | Factorization of discrete-process spectral matrices (Corresp.)abstractIn this correspondence, we consider factoring the spectral matrix of discrete-time systems. The factoring involves finding a matrixH(z)such thatH(z^{-1})H^T (z)equals the spectral matrix and that bothH(z)andH^{-1} (z)are stable and nonanticipatory. The purpose of this paper is to present a new method for obtaining such a spectral factorization. D. Murthy |
IEEE Trans. Inf. Theory | 1 |