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Cognitive Architecture for Circuit Design Innovation with Topological Feature Extraction and Causal Information Mining

dc.identifier.urihttp://hdl.handle.net/11401/78449
dc.description.sponsorshipThis work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree.en_US
dc.formatMonograph
dc.format.mediumElectronic Resourceen_US
dc.typeDissertation
dcterms.available2018-11-12T17:50:23Z
dcterms.contributorDoboli, Alexen_US
dcterms.creatorLi, Hao
dcterms.dateAccepted2018-11-12T17:50:23Z
dcterms.dateSubmitted2018-11-12T17:50:23Z
dcterms.descriptionDepartment of Computer Engineering.en_US
dcterms.extent160 pg.en_US
dcterms.formatMonograph
dcterms.identifierhttp://hdl.handle.net/11401/78449
dcterms.issued2018-01-05
dcterms.issued2018
dcterms.provenanceMade available in DSpace on 2018-11-12T17:50:23Z (GMT). No. of bitstreams: 1 Li_grad.sunysb_0771E_13721.pdf: 1515414 bytes, checksum: 9a02745b8079eaa7601b5436e014627c (MD5) Previous issue date: 2018-01-05en
dcterms.subjectComputer engineering
dcterms.subjectcausality
dcterms.subjectcircuit design
dcterms.subjectcognitive architecture
dcterms.subjectdesign automation
dcterms.subjecttopological feature
dcterms.titleCognitive Architecture for Circuit Design Innovation with Topological Feature Extraction and Causal Information Mining
dcterms.typeDissertation


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