Demo Data from EDBT 2026 / reviewers in the wild / expert
Fu-Min Yuan
dblp:173/1837
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1974
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Automata and formal languages · 46% Coding theory · 46% Information theory · 7% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › error-correcting codes
convolutional codes |
0.0 | 1 | 1974 | Minimal Memory Inverses of Linear Sequential Circuits · IEEE Trans. Computers 1974 |
Coding theory › error-correcting codes › convolutional codes
feedforward inverse |
0.0 | 1 | 1974 | Minimal Memory Inverses of Linear Sequential Circuits · IEEE Trans. Computers 1974 |
Automata and formal languages › finite automata › sequential machines
linear sequential circuits |
0.0 | 1 | 1974 | Minimal Memory Inverses of Linear Sequential Circuits · IEEE Trans. Computers 1974 |
Automata and formal languages › finite automata › sequential machines
sequential circuits |
0.0 | 1 | 1974 | Minimal Memory Inverses of Linear Sequential Circuits · IEEE Trans. Computers 1974 |
Methods — techniques the papers use, named apart from their topics
transfer function matrix · 0.0markov parameters · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1974 | Minimal Memory Inverses of Linear Sequential CircuitsabstractA necessary and sufficient condition for a linear sequential circuit to possess a feedforward inverse is given. This condition for existence of a feedforward inverse is given in terms of the Markov parameters rather than the minors of the transfer function matrix of the linear sequential circuit as has been the case in previous studies on this problem. An upper bound on the required memory of a feedforward inverse for a linear sequential circuit is established in terms of n, the dimension of the state transition matrix and Lo, the inherent delay of the linear sequential circuit. When the original linear sequential circuit is itself feedforward, a stronger upper bound on the memory of a feedforward inverse is established in terms of u, the input memory, k, the number of inputs, and Lo. Both upper bounds on the required inverse memory are shown to be tight in the sense that for each set of possible values of the parameters entering the bound there exists at least one linear sequential circuit whose inverse requires input memory equal to the bound. Finally, a practical and simple algorithm is given to construct a minimal memory inverse. Fu-Min Yuan |
IEEE Trans. Computers | 1 |