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M. A. Murray-Lasso

dblp:16/10978 · 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

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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%

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

TopicWeightPapersLastEvidence papers
Electronic design automation
circuit simulation
0.011967
A digital computer simulation of a class of lumped and/or distributed four ports · DAC 1967
Electronic design automation › circuit simulation
frequency-domain simulation
0.011967
A digital computer simulation of a class of lumped and/or distributed four ports · DAC 1967
Electronic design automation › design for manufacturability
tolerance analysis
0.011967
A digital computer simulation of a class of lumped and/or distributed four ports · DAC 1967

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

random walk optimization · 0.0monte carlo method · 0.0
YearPublicationVenuePosition
1967 A digital computer simulation of a class of lumped and/or distributed four ports
abstract
In this paper a digital computer simulation of a class of lumped and/or distributed four-ports is given. The program is used in predicting the behavior of certain types of lumped and/or distributed directional couplers. The simulation is done in the frequency domain. For this purpose a digital computer program called COPLER is presented. The program obtains a matrix characterizing the four-port at a discrete set of requencies given the values of the discrete components or the values per unit length and lengths of the distributed components plus a code vector showing how they are connected. It also may perform a statistical tolerance analysis using a Monte Carlo method. Taking advantage of such a study it can also optimize the network through a random walk.
M. A. Murray-Lasso
DAC1