{"626314":{"#nid":"626314","#data":{"type":"event","title":"Ph.D. Dissertation Defense - Huan Yu","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E\u003Cem\u003E:\u0026nbsp; \u003C\/em\u003E\u003Cem\u003EBehavioral Modeling of Drivers and Oscillators Using Machine Learning\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Madhavan Swaminathan, ECE, Chair , Advisor\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Sung-Kyu Lim, ECE\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Arijit Raychowdhury, ECE\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Saibal Mukhopadhyay, ECE\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Suresh Sitaraman, ME\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe objective of this dissertation is to develop time-domain behavioral models for I\/O drivers and oscillators for fast simulation and IP protection. For oscillators, augmented neural networks (AugNNs) are proposed to capture the oscillatory behavior of fixed-frequency oscillators and VCOs. When output buffer is included as a part of the oscillator circuit, AugNN-based models are developed taking into account the I\/O behavior of the oscillator. For tunable drivers with pre-emphasis, state-aware weighting functions are proposed, and the dynamic memory characteristics of the driver\u0026rsquo;s output stage are captured using recurrent neural networks (RNNs). The behavior of the tunable control parameters is captured. Furthermore, a transition-variational model is discussed for the modeling of I\/O drivers under overclocking conditions. The proposed models are compatible with Verilog-A.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Behavioral Modeling of Drivers and Oscillators Using Machine Learning "}],"uid":"28475","created_gmt":"2019-09-17 21:12:11","changed_gmt":"2019-09-17 21:12:11","author":"Daniela Staiculescu","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-10-01T14:30:00-04:00","event_time_end":"2019-10-01T16:30:00-04:00","event_time_end_last":"2019-10-01T16:30:00-04:00","gmt_time_start":"2019-10-01 18:30:00","gmt_time_end":"2019-10-01 20:30:00","gmt_time_end_last":"2019-10-01 20:30:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"434381","name":"ECE Ph.D. Dissertation Defenses"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"},{"id":"1808","name":"graduate students"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}