This thesis proposes a digital artificial neuron which uses only digital logic. The purpose is to create a hardware neuron on a digital device. While conventional neurons use real valued software implemented transfer functions and threshold values to determine the output, the proposed neuron converts inputs into square waves of frequencies determined by weights, and the time that the input waves require to produce a certain pattern is used to determine the output. This neuron was tested on a software simulator and successfully implemented on a Field Programmable Gate Array (FPGA) to prove its viability.
","abstract_html":"<p>This thesis proposes a digital artificial neuron which uses only digital logic. The purpose is to create a hardware neuron on a digital device. While conventional neurons use real valued software implemented transfer functions and threshold values to determine the output, the proposed neuron converts inputs into square waves of frequencies determined by weights, and the time that the input waves require to produce a certain pattern is used to determine the output. This neuron was tested on a software simulator and successfully implemented on a Field Programmable Gate Array (FPGA) to prove its viability.</p>","abstract_has_math":false,"creators":["Ellis, David J."],"institution":null,"degree_name":"Master of Science (MS) in Computer Science","degree_level":"Thesis: EWU Only","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Dr. Kosuke Imamura, PhD","Dr. Carol Taylor, PhD","Doris Munson M.L.S."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-01T08:00:00Z","date_published":"2014-01-01T08:00:00Z","updated_at":"2026-07-24T02:12:26Z","subjects":["Neural networks (Computer science)","Evolutionary computation","Field programmable gate arrays","Computer Sciences"],"languages":[],"rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/1","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr. Kosuke Imamura, PhD","Dr. Carol Taylor, PhD","Doris Munson M.L.S."]},{"key":"dc:creator","label":"Author","values":["Ellis, David J."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis: EWU Only"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Neural networks (Computer science)","Evolutionary computation","Field programmable gate arrays","Computer Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access perpetually restricted to EWU users with an active EWU NetID"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/1"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis proposes a digital artificial neuron which uses only digital logic. The purpose is to create a hardware neuron on a digital device. While conventional neurons use real valued software implemented transfer functions and threshold values to determine the output, the proposed neuron converts inputs into square waves of frequencies determined by weights, and the time that the input waves require to produce a certain pattern is used to determine the output. This neuron was tested on a software simulator and successfully implemented on a Field Programmable Gate Array (FPGA) to prove its viability.
"]},{"key":"dc:title","label":"Title","values":["Artificial Frequency Match Neuron Implemented with Digital Logic"]}]}],"canonical_facts":{"dc:contributor":["Dr. Kosuke Imamura, PhD","Dr. Carol Taylor, PhD","Doris Munson M.L.S."],"dc:creator":["Ellis, David J."],"dc:description.abstract":["This thesis proposes a digital artificial neuron which uses only digital logic. The purpose is to create a hardware neuron on a digital device. While conventional neurons use real valued software implemented transfer functions and threshold values to determine the output, the proposed neuron converts inputs into square waves of frequencies determined by weights, and the time that the input waves require to produce a certain pattern is used to determine the output. This neuron was tested on a software simulator and successfully implemented on a Field Programmable Gate Array (FPGA) to prove its viability.
"],"dc:identifier":["https://dc.ewu.edu/theses/1"],"dc:rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"dc:subject":["Neural networks (Computer science)","Evolutionary computation","Field programmable gate arrays","Computer Sciences"],"dc:title":["Artificial Frequency Match Neuron Implemented with Digital Logic"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis: EWU Only"],"thesis:degree_name":["Master of Science (MS) in Computer Science"]},"updated_at":"2026-07-24T02:12:26Z"}