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Antonio M. Lepschy

dblp:50/1856 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 1986
—ORCID · none

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

Human-computer interaction and ubiquitous computing · 1Theory 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
Information theory · 100%

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

TopicWeightPapersLastEvidence papers
Information theory › signal processing
spectral estimation		 0.011986
Comments, with reply, on 'ARMA spectral estimation of time series with missing observations' by B. Porat and B. Friedlander · IEEE Trans. Inf. Theory 1986
Information theory › statistical inference
missing data		 0.011986
Comments, with reply, on 'ARMA spectral estimation of time series with missing observations' by B. Porat and B. Friedlander · IEEE Trans. Inf. Theory 1986
Information theory › probability theory › stochastic processes
time series analysis		 0.011986
Comments, with reply, on 'ARMA spectral estimation of time series with missing observations' by B. Porat and B. Friedlander · IEEE Trans. Inf. Theory 1986

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

partial fraction expansion · 0.0
YearPublicationVenuePosition
1986 Comments, with reply, on 'ARMA spectral estimation of time series with missing observations' by B. Porat and B. Friedlander
abstract
A variant to a recently proposed autoregressive moving average (ARMA) spectrum estimation technique for time series with gapped data is suggested. It is based on the partial fraction expansion of the power spectrum and exhibits some computational and operational advantages.
Antonio M. Lepschy, Gian Antonio Mian, Umberto Viaro
 IEEE Trans. Inf. Theory1
1986 On the Relationship between Forrester's Schematics and Compartmental Graphs
abstract
Graphic representations may be considered as a tool for deriving a mathematical model from a qualitative description. Forrester's schematics and compartmental graphs are examined from this point of view. Their similarities and differences are then discussed. Two examples taken from the system dynamics literature help clarify the characteristics of both representations.
Claudio Cobelli, Antonio M. Lepschy, Giorgio Romanin-Jacur, Umberto Viaro
 IEEE Trans. Syst. Man Cybern.2