{"id":"https://openalex.org/W2029035490","doi":"https://doi.org/10.1109/icc.2013.6655196","title":"Lower bound for ML sequence detection in ISI channels with Gauss Markov noise","display_name":"Lower bound for ML sequence detection in ISI channels with Gauss Markov noise","publication_year":2013,"publication_date":"2013-06-01","ids":{"openalex":"https://openalex.org/W2029035490","doi":"https://doi.org/10.1109/icc.2013.6655196","mag":"2029035490"},"language":"en","primary_location":{"id":"doi:10.1109/icc.2013.6655196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2013.6655196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Communications (ICC)","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/A5049950091","display_name":"Naveen Kumar","orcid":"https://orcid.org/0000-0001-5590-4590"},"institutions":[{"id":"https://openalex.org/I10654025","display_name":"SK Group (United States)","ror":"https://ror.org/00qajw440","country_code":"US","type":"company","lineage":["https://openalex.org/I10654025","https://openalex.org/I134353371"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Naveen Kumar","raw_affiliation_strings":["SK Hynix Memory Solutions Inc, San Jose, CA",", SK Hynix Memory Solutions Inc., San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"SK Hynix Memory Solutions Inc, San Jose, CA","institution_ids":["https://openalex.org/I10654025"]},{"raw_affiliation_string":", SK Hynix Memory Solutions Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I10654025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5049950091"],"corresponding_institution_ids":["https://openalex.org/I10654025"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12542626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4063","last_page":"4067"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T12162","display_name":"Cellular Automata and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.8817940950393677},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.7765374183654785},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6348683834075928},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5929009318351746},{"id":"https://openalex.org/keywords/intersymbol-interference","display_name":"Intersymbol interference","score":0.5623987913131714},{"id":"https://openalex.org/keywords/trellis","display_name":"Trellis (graph)","score":0.49619919061660767},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.49374160170555115},{"id":"https://openalex.org/keywords/viterbi-decoder","display_name":"Viterbi decoder","score":0.4633166790008545},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4237544536590576},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41250449419021606},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41053563356399536},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4105130136013031},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.2389228343963623},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19249975681304932},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.08215305209159851},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.0680161714553833}],"concepts":[{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.8817940950393677},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.7765374183654785},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6348683834075928},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5929009318351746},{"id":"https://openalex.org/C97812054","wikidata":"https://www.wikidata.org/wiki/Q2166055","display_name":"Intersymbol interference","level":3,"score":0.5623987913131714},{"id":"https://openalex.org/C2781235587","wikidata":"https://www.wikidata.org/wiki/Q7838009","display_name":"Trellis (graph)","level":3,"score":0.49619919061660767},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.49374160170555115},{"id":"https://openalex.org/C117379686","wikidata":"https://www.wikidata.org/wiki/Q6996459","display_name":"Viterbi decoder","level":3,"score":0.4633166790008545},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4237544536590576},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41250449419021606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41053563356399536},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4105130136013031},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.2389228343963623},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19249975681304932},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.08215305209159851},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0680161714553833},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc.2013.6655196","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc.2013.6655196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Communications (ICC)","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":15,"referenced_works":["https://openalex.org/W1572157493","https://openalex.org/W1989008275","https://openalex.org/W1991133427","https://openalex.org/W2054437021","https://openalex.org/W2067999338","https://openalex.org/W2099932638","https://openalex.org/W2124155561","https://openalex.org/W2128101805","https://openalex.org/W2131086249","https://openalex.org/W2139738685","https://openalex.org/W2142384583","https://openalex.org/W2148502757","https://openalex.org/W2159124867","https://openalex.org/W2162877755","https://openalex.org/W4240386132"],"related_works":["https://openalex.org/W2102309991","https://openalex.org/W1795315578","https://openalex.org/W2373954783","https://openalex.org/W2024650855","https://openalex.org/W2133857928","https://openalex.org/W2101868111","https://openalex.org/W2146383045","https://openalex.org/W2110622634","https://openalex.org/W2163418885","https://openalex.org/W1578429744"],"abstract_inverted_index":{"In":[0,86,147],"past,":[1],"inter-symbol":[2],"interference":[3],"(ISI)":[4],"channels":[5,19,35,98],"with":[6,99],"data":[7,25,100],"dependent":[8,101],"Gauss":[9],"Markov":[10],"noise":[11],"have":[12],"been":[13,65],"prevalently":[14],"used":[15],"to":[16],"model":[17],"read":[18],"for":[20,163],"magnetic":[21],"recording":[22],"and":[23,120,137,143,193],"other":[24],"storage":[26],"systems.":[27],"The":[28],"maximum":[29],"likelihood":[30],"sequence":[31,119,124],"detection":[32],"in":[33,60,204],"such":[34],"is":[36,152,202],"solved":[37],"using":[38],"the":[39,43,52,57,73,78,94,110,116,121,141,144,150,156,164,177,187,190,196],"Viterbi":[40,58],"algorithm.":[41],"However,":[42],"problem":[44],"of":[45,56,93,96,132,140,158,171,189],"finding":[46,172],"an":[47],"analytical":[48],"lower":[49,75,107,174,191,198],"bound":[50,76,79,108,165,175,192,199],"on":[51,109,135,176,200],"bit":[53,118,123],"error":[54,84,112,159],"rate":[55],"detector":[59],"this":[61,87,148],"case":[62],"has":[63],"not":[64,71],"fully":[66],"investigated.":[67],"Current":[68],"techniques":[69],"do":[70],"give":[72],"tight":[74,203],"as":[77,129],"computation":[80],"involves":[81],"only":[82],"minimum-length":[83],"events.":[85],"work,":[88],"we":[89],"consider":[90],"a":[91,106,130,169,173,181,205],"subset":[92],"class":[95],"ISI":[97],"Gauss-Markov":[102],"noise.":[103],"We":[104,167],"derive":[105],"pairwise":[111],"probability":[113],"(PEP)":[114],"between":[115],"correct":[117,142],"estimated":[122,145],"that":[125,195],"can":[126],"be":[127],"expressed":[128],"product":[131,182],"functions":[133],"depending":[134],"current":[136],"previous":[138],"states":[139],"sequence.":[146],"case,":[149],"PEP":[151],"asymmetric":[153],"which":[154],"precludes":[155],"usage":[157],"state":[160],"diagram":[161],"method":[162,170],"computation.":[166],"present":[168],"BER":[178,201],"through":[179],"constructing":[180],"trellis.":[183],"Simulations":[184],"results":[185],"corroborate":[186],"analysis":[188],"demonstrate":[194],"analytic":[197],"high":[206],"SNR":[207],"regime.":[208]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}