Paul Yatrou

dblp:142/0913 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1988
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 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.

Computer graphics and multimedia
1 paper
Audio and music processing · 100%
Theoretical computer science
1 paper
Coding theory · 100%
Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › speech coding
adaptive differential pulse code modulation
0.011988
Ensuring predictor tracking in ADPCM speech coders under noisy transmission conditions · IEEE J. Sel. Areas Commun. 1988
Audio and music processing
speech coding
0.011988
Ensuring predictor tracking in ADPCM speech coders under noisy transmission conditions · IEEE J. Sel. Areas Commun. 1988
Coding theory › source coding
predictive coding
0.011988
Ensuring predictor tracking in ADPCM speech coders under noisy transmission conditions · IEEE J. Sel. Areas Commun. 1988
Physical-layer communications
signal processing for communications
0.011988
Ensuring predictor tracking in ADPCM speech coders under noisy transmission conditions · IEEE J. Sel. Areas Commun. 1988

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

residual-signal-driven adaptation · 0.0lattice prediction · 0.0
YearPublicationVenuePosition
1988 Ensuring predictor tracking in ADPCM speech coders under noisy transmission conditions
abstract
The problem of predictor mistracking for narrowband signals in backward adaptive ADPCM (adaptive digital pulse code modulation) speech coders is shown to arise as a result of feedback from the signal reconstruction filter to the predictor adaptation process. A class of residual-signal-driven lattice predictors (PR) is defined that guarantees tracking for all signals without regard to the order of prediction. The LR predictor enhances speech and DTMF (dual-tone multifrequency) signal transmission performance in the presence of transmission errors. Under error-free transmission conditions, a segmental SNR (signal-to-noise ratio) drop for speech of nearly 2 dB may be encountered for the LR predictor relative to the classical signal-drive lattice predictor. In most practical telecommunication applications, however, this degradation is outweighed by the improved robustness of the predictor.>
Paul Yatrou, Paul Mermelstein
IEEE J. Sel. Areas Commun.1