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Benjamin M. Eisenstadt

dblp:182/0099 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1961
—ORCID · none

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

Systems, architecture and hardware · 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 · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › sequences
periodic binary sequence		 0.011961
Autocorrelations for Boolean Functions of Noiselike Periodic Sequences · IRE Trans. Electron. Comput. 1961
Coding theory › sequences
pseudorandom sequences		 0.011961
Autocorrelations for Boolean Functions of Noiselike Periodic Sequences · IRE Trans. Electron. Comput. 1961

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

boolean function analysis · 0.0
YearPublicationVenuePosition
1961 Autocorrelations for Boolean Functions of Noiselike Periodic Sequences
abstract
One method of generating a waveform whose correlation function resembles that of noise is by means of combinations of periodic binary sequences. In this paper the properties of the correlation function for arbitrary functions of n periodic binary sequences are investigated. An especially simple formulation is obtained when each binary variable in all the sequences has equal probability of being 0 or 1. For this case, it is shown that there are only two functions which result in a correlation function like true purely random noise. One of these two functions corresponds to addition modulo 2. Also, the correlation for the case of a random function of n sequences is derived. Finally, expressions are obtained for the number of degenerate Boolean functions.
Benjamin M. Eisenstadt, Bernhard Gold
 IRE Trans. Electron. Comput.1