{"id":{"repo_id":"gmu","oai_identifier":"oai:MARS:1920/8990"},"canonical_url":"https://search.dev.ndltd.org/etd/gmu/oai:MARS:1920/8990","repository":{"repo_id":"gmu","name":"George Mason University","base_url":"https://mars.gmu.edu/server/oai/request"},"display":{"title":"Parameter Estimation in Hybrid Dynamical Systems with Application to Neuronal Models","abstract":"Analysis and recreation of brain dynamics has been identified as one of the greatest scientific challenge of this century. Detection of electrical impulses in the brain was the first step towards understanding how it functions. An interconnected network of neurons relay information and communicate with one another through these impulses also referred to as 'spikes'. Knowledge of the spiking behavior and connectivity in different regions of the brain will help in the diagnosis and treatment of neurological disorders such as epilepsy and Parkinsons disease. 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There are also efforts to develop intelligent algorithms inspired by the functioning of the brain and build efficient processing and computing units.","abstract_has_math":false,"creators":["Mitra, Anish"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-08","date_published":"2014-08","updated_at":"2026-07-27T19:51:52Z","subjects":["Electrical engineering","Biomedical engineering","Hybrid Dynamical Systems","Neuron Spiking Models","Optimization","Parameter Estimation","System Identification"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/8990"],"render_values":[{"text":"hdl:1920/8990","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2014-08"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical engineering","Biomedical engineering","Hybrid Dynamical Systems","Neuron Spiking Models","Optimization","Parameter Estimation","System Identification"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/8990"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.other","label":"Dc Description Other","values":["Analysis and recreation of brain dynamics has been identified as one of the greatest scientific challenge of this century. Detection of electrical impulses in the brain was the first step towards understanding how it functions. An interconnected network of neurons relay information and communicate with one another through these impulses also referred to as 'spikes'. Knowledge of the spiking behavior and connectivity in different regions of the brain will help in the diagnosis and treatment of neurological disorders such as epilepsy and Parkinsons disease. There are also efforts to develop intelligent algorithms inspired by the functioning of the brain and build efficient processing and computing units."]},{"key":"dc:title","label":"Title","values":["Parameter Estimation in Hybrid Dynamical Systems with Application to Neuronal Models"]}]}],"canonical_facts":{"dc:date.issued":["2014-08"],"dc:description.other":["Analysis and recreation of brain dynamics has been identified as one of the greatest scientific challenge of this century. Detection of electrical impulses in the brain was the first step towards understanding how it functions. An interconnected network of neurons relay information and communicate with one another through these impulses also referred to as 'spikes'. Knowledge of the spiking behavior and connectivity in different regions of the brain will help in the diagnosis and treatment of neurological disorders such as epilepsy and Parkinsons disease. There are also efforts to develop intelligent algorithms inspired by the functioning of the brain and build efficient processing and computing units."],"dc:identifier":["hdl:1920/8990"],"dc:subject":["Electrical engineering","Biomedical engineering","Hybrid Dynamical Systems","Neuron Spiking Models","Optimization","Parameter Estimation","System Identification"],"dc:title":["Parameter Estimation in Hybrid Dynamical Systems with Application to Neuronal Models"],"dc:type":["Dissertation"]},"updated_at":"2026-07-27T19:51:52Z"}