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VLDB 2026 Research / reviewers in the wild / expert

Wolfgang Mauersberger

dblp:45/5509 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 1981
—ORCID · none

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

Theory of computation · 2 · 2 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
2 papers
Coding theory · 88% Information theory · 12%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › source coding
quantization		 0.021981
An analytic function describing the error performance of optimum quantizers · IEEE Trans. Inf. Theory 1981
Experimental results on the performance of mismatched quantizers · IEEE Trans. Inf. Theory 1979
Coding theory
source coding		 0.021981
An analytic function describing the error performance of optimum quantizers · IEEE Trans. Inf. Theory 1981
Experimental results on the performance of mismatched quantizers · IEEE Trans. Inf. Theory 1979
Coding theory › source coding › quantization
optimal quantization		 0.011981
An analytic function describing the error performance of optimum quantizers · IEEE Trans. Inf. Theory 1981
Coding theory › source coding › quantization › quantization theory
quantization error		 0.011981
An analytic function describing the error performance of optimum quantizers · IEEE Trans. Inf. Theory 1981
Information theory › estimation theory › mean-square estimation
minimum mean-square error		 0.011979
Experimental results on the performance of mismatched quantizers · IEEE Trans. Inf. Theory 1979

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

analytic approximation · 0.0laplacian distribution · 0.0gaussian distribution · 0.0gamma distribution · 0.0
YearPublicationVenuePosition
1981 An analytic function describing the error performance of optimum quantizers
abstract
For optimizing or analyzing digital source coding systems, a model for the mean square quantizing error as a function of the number of levels is necessary. An analytic approximation function is presented which is valid for a wide range of important probability density functions.
Wolfgang Mauersberger
 IEEE Trans. Inf. Theory1
1979 Experimental results on the performance of mismatched quantizers
abstract
Quantizers for digital coding systems are usually optimized with respect to a model of the probability density function of the random variable to be quantized. Thus a mismatch of the quantizer relative to the actual statistics of the random variable may be unavoidable. This paper presents the results of an experimental investigation of three types of mismatch. For the modeling of the source statistics, the gamma-, Laplacian-, and Gaussian-distribution are used. The optimization of the quarttizers is carried out with respect to the minimum mean-square error criterion.
Wolfgang Mauersberger
 IEEE Trans. Inf. Theory1