System level performance analysis – the SymTA/S approach

338 indexed citations
published 2005
Journal
IEE Proceedings - Computers and Digital Techniques

Countries where authors are citing System level performance analysis – the SymTA/S approach

Specialization
Citations

This map shows the geographic impact of System level performance analysis – the SymTA/S approach. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by System level performance analysis – the SymTA/S approach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites System level performance analysis – the SymTA/S approach more than expected).

Fields of papers citing System level performance analysis – the SymTA/S approach

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of System level performance analysis – the SymTA/S approach. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the System level performance analysis – the SymTA/S approach.

About System level performance analysis – the SymTA/S approach

This paper, published in 2005, received 338 indexed citations . Written by Rafik Henia, Arne Hamann, Marek Jersak, Razvan Racu and Kai Richter covering the research area of Hardware and Architecture and Computer Networks and Communications. It is primarily cited by scholars working on Hardware and Architecture (314 citations), Computer Networks and Communications (176 citations) and Computational Theory and Mathematics (89 citations). Published in IEE Proceedings - Computers and Digital Techniques.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1049/ip-cdt:20045088.

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