{"id":"https://openalex.org/W2534669422","doi":"https://doi.org/10.1109/ebccsp.2016.7605247","title":"Geometric numeric integration in the event-driven measurement method","display_name":"Geometric numeric integration in the event-driven measurement method","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2534669422","doi":"https://doi.org/10.1109/ebccsp.2016.7605247","mag":"2534669422"},"language":"en","primary_location":{"id":"doi:10.1109/ebccsp.2016.7605247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ebccsp.2016.7605247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Second International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024476912","display_name":"Mikhail Simonov","orcid":"https://orcid.org/0000-0002-5711-6130"},"institutions":[{"id":"https://openalex.org/I2800599128","display_name":"Istituto Superiore Mario Boella","ror":"https://ror.org/05y6jfx28","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2800599128","https://openalex.org/I4210155299"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Mikhail Simonov","raw_affiliation_strings":["Istituto Superiore Mario Boella, Turin, Italy"],"affiliations":[{"raw_affiliation_string":"Istituto Superiore Mario Boella, Turin, Italy","institution_ids":["https://openalex.org/I2800599128"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5024476912"],"corresponding_institution_ids":["https://openalex.org/I2800599128"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13080203,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9729999899864197,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.97079998254776,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.628317654132843},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6142435073852539},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.6036847233772278},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5836954116821289},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.56884765625},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5315463542938232},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5133739709854126},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.49185800552368164},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.48460397124290466},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.4835972189903259},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.46185410022735596},{"id":"https://openalex.org/keywords/lebesgue-integration","display_name":"Lebesgue integration","score":0.4464791715145111},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3873467445373535},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3461127281188965},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2934315800666809},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1972896158695221},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.19601306319236755},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.186526358127594}],"concepts":[{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.628317654132843},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6142435073852539},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.6036847233772278},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5836954116821289},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.56884765625},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5315463542938232},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5133739709854126},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.49185800552368164},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.48460397124290466},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.4835972189903259},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.46185410022735596},{"id":"https://openalex.org/C14158598","wikidata":"https://www.wikidata.org/wiki/Q853831","display_name":"Lebesgue integration","level":2,"score":0.4464791715145111},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3873467445373535},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3461127281188965},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2934315800666809},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1972896158695221},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.19601306319236755},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.186526358127594},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ebccsp.2016.7605247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ebccsp.2016.7605247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Second International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1487782069","https://openalex.org/W1931182496","https://openalex.org/W1964873984","https://openalex.org/W1995520632","https://openalex.org/W2028788479","https://openalex.org/W2031598719","https://openalex.org/W2091311817","https://openalex.org/W2158537680","https://openalex.org/W2284462733","https://openalex.org/W2547723086","https://openalex.org/W3101408971","https://openalex.org/W6695905061"],"related_works":["https://openalex.org/W16753908","https://openalex.org/W4235381733","https://openalex.org/W4293463489","https://openalex.org/W2324070114","https://openalex.org/W2347623497","https://openalex.org/W2355022049","https://openalex.org/W2060429446","https://openalex.org/W1625117912","https://openalex.org/W2741782512","https://openalex.org/W2862724827"],"abstract_inverted_index":{"The":[0,111],"Event-Driven":[1],"Metering":[2],"(EDM)":[3],"method":[4],"is":[5,113],"about":[6],"data-driven":[7,108],"compression":[8],"of":[9,17,22,35,40,65,74,87,94,125],"the":[10,15,18,23,32,36,45,50,55,59,63,71,75,84,99,129,135],"measurement":[11],"data":[12,47,80],"based":[13],"on":[14],"replacement":[16],"original":[19,136],"arbitrary":[20],"shape":[21,120],"load":[24,119],"by":[25],"a":[26,92,118,122],"simplified":[27],"polygonal":[28],"line":[29],"that":[30,77,116],"represents":[31],"same":[33,130],"values":[34],"energy":[37,89,100,131],"per":[38],"interval":[39],"time.":[41],"EDM":[42],"algorithm":[43],"receives":[44],"Shannon":[46],"samples":[48],"encoding":[49],"local":[51],"measurements":[52],"and":[53,97],"reports":[54],"pre-processed":[56],"knowledge":[57],"to":[58,105],"controlling":[60],"hosts":[61],"in":[62,91,103,134],"form":[64],"Lebesgue-based":[66],"events.":[67],"This":[68],"article":[69],"explains":[70],"mathematical":[72],"foundations":[73],"invention":[76],"allows":[78],"improved":[79],"efficiency.":[81],"Method":[82],"decomposes":[83],"global":[85],"behavior":[86],"an":[88,114],"system":[90],"sequence":[93,124],"linearized":[95],"chunks":[96],"exploits":[98],"conservation":[101],"law":[102],"order":[104],"set":[106],"up":[107],"geometric":[109],"integration.":[110],"result":[112],"operator":[115],"maps":[117],"into":[121],"data-efficient":[123],"tokens":[126],"representing":[127],"exactly":[128],"quantities":[132],"as":[133],"pattern.":[137]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}