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David Kryskowski

dblp:200/5619 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1985
—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 graphics and multimedia
1 paper
Audio and music processing · 100%
Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing
speech coding
0.011985
Stack Algorithm Speech Encoding with Fixed and Variable Symbol Release Rules · IEEE Trans. Commun. 1985
Coding theory
source coding
0.011985
Stack Algorithm Speech Encoding with Fixed and Variable Symbol Release Rules · IEEE Trans. Commun. 1985
Coding theory › interactive communication
tree codes
0.011985
Stack Algorithm Speech Encoding with Fixed and Variable Symbol Release Rules · IEEE Trans. Commun. 1985

Methods — techniques the papers use, named apart from their topics

symbol release rules · 0.0AVL tree data structure · 0.0
YearPublicationVenuePosition
1985 Stack Algorithm Speech Encoding with Fixed and Variable Symbol Release Rules
abstract
Tree codes find wide use in a variety of problems such as source encoding, sequential decoding, pattern recognition, and related fields. Efficient algorithms exist to explore the code trees and are well documented in the literature. All of these algorithms search code trees in an incremental manner, releasing a path map symbol at a time. A recent work has investigated the effect of releasing multiple symbols on the performance of the(M, L)algorithm used with speech. Here we investigate the effect of multiple symbol release rules on the performance of the stack algorithm in the context of speech encoding. We show that significant computational reduction can result with the use of such rules. We use an efficient data structure, the AVL tree data structure, to store code tree paths.
Seshadri Mohan, Chih-Min Lin, David Kryskowski
IEEE Trans. Commun.3