{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/113925"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/113925","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Signal integrity analysis of interconnect systems using neural networks","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. 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The analysis of the signal and power delivery networks of the complete high-speed links is often performed in time domain using a time-consuming approach of the time marching methods. However, the interconnect systems are accurately characterized in frequency domain. Analyzing interconnect systems in time domain without order reduction results in extreme inefficiency and inaccuracy. Therefore, this thesis discusses an efficient and unsupervised method for reducing the order of interconnect system for subsequent time domain simulation."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Signal integrity analysis of interconnect systems using neural networks"]}]}],"canonical_facts":{"dc:contributor":["Schutt-Ainé, José"],"dc:creator":["Konduru, Juhitha"],"dc:date":["2022-04-29T21:35:52Z","2021-12","2021-12-08"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. 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