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Willis C. Kellogg

dblp:134/3839 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1967
—ORCID · none

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

Theory of computation · 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
Coding theory · 70% Information theory · 30%

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

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes › block codes › linear code
parity-check matrix
0.011967
Information rates in sampling and quantization · IEEE Trans. Inf. Theory 1967
Coding theory › source coding
quantization
0.011967
Information rates in sampling and quantization · IEEE Trans. Inf. Theory 1967
Coding theory › source coding
rate-distortion theory
0.011967
Information rates in sampling and quantization · IEEE Trans. Inf. Theory 1967
Information theory › signal processing › signal representation
sampling and quantization
0.011967
Information rates in sampling and quantization · IEEE Trans. Inf. Theory 1967
Information theory
channel capacity
0.011967
Information rates in sampling and quantization · IEEE Trans. Inf. Theory 1967

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

numerical convolution · 0.0bivariate normal integration · 0.0
YearPublicationVenuePosition
1967 Information rates in sampling and quantization
abstract
A computer-aided analysis of a digital communications system has been conducted. Salient results compare the performance of approximately optimum PCM systems with the rate-distortion function, under the assumptions of Gaussian inputs and mean-square-error distortion measure. The calculated distortion is greater than the theoretical minimum by two or three decibels in most cases. The results presented also illuminate the tradeoff between sampling rate and number of quantization levels in a channel of fixed capacity. The presampling and reconstruction filters are represented in the computer by their impulse responses; that is, filtering of signals is accomplished by evaluating the convolution integrals numerically. Impulse responses with durations of20sample times or fewer are long enough to model most known results in optimum filtering of sampled stationary random functions. Procedures are described for computing the autocorrelation function of the quantizer output, and the cross correlation between the quantizer output and a signal correlated with the input. The procedure adopted is the naive one of integrating numerically the appropriate bivariate normal distribution.
Willis C. Kellogg
IEEE Trans. Inf. Theory1