H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities

318 indexed citations

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This paper, published in 2008, received 318 indexed citations. Written by Zidong Wang, Yurong Liu and Xiaohui Liu covering the research area of Control and Systems Engineering and Artificial Intelligence. It is primarily cited by scholars working on Control and Systems Engineering (269 citations), Computer Networks and Communications (160 citations) and Artificial Intelligence (71 citations). Published in Automatica.

Countries where authors are citing H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities

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This map shows the geographic impact of H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities. 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 H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities more than expected).

Fields of papers citing H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the H filtering for uncertain stochastic time-delay systems with sector-bounded nonlinearities.

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/10.1016/j.automatica.2007.09.016.

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