Demo Data from VLDB 2026 / reviewers in the wild / expert
Alexander V. Kuznetsov 0002
dblp:78/4834-2
· DBLP profile ↗
3ranked-venue papers
3as first author
0since 2021 · last 1996
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 3 · 3 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
3 papers |
Coding theory · 51% Information theory · 49% |
Topics — the 12 heaviest of 13, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information theory › communication channels › channel models
channels with memory |
0.0 | 1 | 1996 | On the undetected error probability of linear block codes on channels with memory · IEEE Trans. Inf. Theory 1996 |
Coding theory › error-correcting codes
error detection |
0.0 | 1 | 1996 | On the undetected error probability of linear block codes on channels with memory · IEEE Trans. Inf. Theory 1996 |
Information theory › channel capacity › state-dependent channel › finite-state channel
gilbert-elliott channel |
0.0 | 1 | 1996 | On the undetected error probability of linear block codes on channels with memory · IEEE Trans. Inf. Theory 1996 |
Coding theory › error-correcting codes › block codes
linear block codes |
0.0 | 1 | 1996 | On the undetected error probability of linear block codes on channels with memory · IEEE Trans. Inf. Theory 1996 |
Information theory › communication channels › channel models › channels with memory
markov channels |
0.0 | 1 | 1996 | On the undetected error probability of linear block codes on channels with memory · IEEE Trans. Inf. Theory 1996 |
Coding theory › error-correcting codes › error detection
undetected error probability |
0.0 | 1 | 1996 | On the undetected error probability of linear block codes on channels with memory · IEEE Trans. Inf. Theory 1996 |
Information theory
channel capacity |
0.0 | 1 | 1994 | On the general defective channel with informed encoder and capacities of some constrained memories · IEEE Trans. Inf. Theory 1994 |
Information theory › communication channels
channel models |
0.0 | 1 | 1994 | On the general defective channel with informed encoder and capacities of some constrained memories · IEEE Trans. Inf. Theory 1994 |
Coding theory › error-correcting codes
block codes |
0.0 | 1 | 1993 | A coding scheme for single peak-shift correction in (d, k)-constrained channels · IEEE Trans. Inf. Theory 1993 |
Coding theory
constrained coding |
0.0 | 1 | 1993 | A coding scheme for single peak-shift correction in (d, k)-constrained channels · IEEE Trans. Inf. Theory 1993 |
Coding theory › error-correcting codes › storage coding
write-once memory |
0.0 | 1 | 1994 | On the general defective channel with informed encoder and capacities of some constrained memories · IEEE Trans. Inf. Theory 1994 |
Coding theory › constrained coding
runlength-limited codes |
0.0 | 1 | 1993 | A coding scheme for single peak-shift correction in (d, k)-constrained channels · IEEE Trans. Inf. Theory 1993 |
Methods — techniques the papers use, named apart from their topics
trellis representation · 0.0recursive computation · 0.0capacity bounds · 0.0enumeration-free encoding · 0.0block code construction · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | On the undetected error probability of linear block codes on channels with memoryabstractWe derive an upper bound on the undetected error probability of binary (n, k) block codes used on channels with memory described by Markov distributions. This bound is a generalization of the bound presented by Kasami et al. (1984) for the binary symmetric channel, and is given as an average value of some function of the composition of the state sequence of the channel. It can be extended in particular cases of Markov-type channels. As an example, such an extended bound is given for the Gilbert-Elliott (1960, 1963) channel and Markov channels with deterministic errors determined by the state. We develop a recursive technique for the exact calculation of the undetected error probability of an arbitrary linear block code used on a Markov-type channel. This technique is based on the trellis representation of block codes described by Wolf (1978). Results of some computations are presented. Alexander V. Kuznetsov 0002, Francis Swarts, A. J. Han Vinck, Hendrik C. Ferreira |
IEEE Trans. Inf. Theory | 1 |
| 1994 | On the general defective channel with informed encoder and capacities of some constrained memoriesabstractFrom an information-theoretical point of view the write once memory (WOM), the unidirectional memory (WUM), the write isolated memory (WIM), the memory with address faults (MAF), Blackwell's broadcast channel, and some other constrained memories and channels with an informed encoder can be considered as particular cases of the general defective channel (GDC) introduced by Kuznetsov (1983) as a generalization of a memory with defects. Using the concept of the GDC we consider a unified approach to the investigation of different types of natural and artificial channels with a finite number of states known to the encoder, but unknown to the decoder. To illustrate the usefulness of this approach we derive the capacities of the above-mentioned constrained memories (WOM, WUM, WIM, MAF) as corollaries of lower and upper bounds for the number of messages transmitted over the GDC.> Alexander V. Kuznetsov 0002, A. J. Han Vinck |
IEEE Trans. Inf. Theory | 1 |
| 1993 | A coding scheme for single peak-shift correction in (d, k)-constrained channelsabstractA two step coding scheme for peak-shift correction in (d, k)-constrained sequences is described. The first step is based on q-ary (q=k-d+1 is a prime) block codes that allow correction of specific types of double errors caused by single peak-shifts. The second step is a simple conversion of q-ary symbols to binary strings of the type 00. . .01. The concatenation of these strings satisfies the (d,k)-constraint within the codeword and in concatenation with neighboring words. The length of the codewords is controlled and, if necessary, can be fixed. The rate R/sub 1/ of the overall encoding approaches (2 log/sub 2/ (k-d+1)/(k+d+2) for large codeword lengths. Codes for correction of peak-shift, deletions, and insertions of zeros are presented as well. Encoding and decoding are done by simple algorithms without using look-up tables, enumeration or denumeration procedures and, therefore, the codelength may be large.> Alexander V. Kuznetsov 0002, A. J. Han Vinck |
IEEE Trans. Inf. Theory | 1 |