{"id":"https://openalex.org/W7143374265","doi":"https://doi.org/10.48550/arxiv.2603.26344","title":"A Power-Weighted Noncentral Complex Gaussian Distribution","display_name":"A Power-Weighted Noncentral Complex Gaussian Distribution","publication_year":2026,"publication_date":"2026-03-27","ids":{"openalex":"https://openalex.org/W7143374265","doi":"https://doi.org/10.48550/arxiv.2603.26344"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.26344","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26344","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.26344","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130987401","display_name":"Toru Nakashika","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nakashika, Toru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5130987401"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.6478000283241272,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.6478000283241272,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.056299999356269836,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.04899999871850014,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/amplitude","display_name":"Amplitude","score":0.6107000112533569},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5999000072479248},{"id":"https://openalex.org/keywords/spectral-density","display_name":"Spectral density","score":0.4921000003814697},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4772000014781952},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47440001368522644},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.453900009393692},{"id":"https://openalex.org/keywords/complex-normal-distribution","display_name":"Complex normal distribution","score":0.42750000953674316},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4242999851703644},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4212000072002411}],"concepts":[{"id":"https://openalex.org/C180205008","wikidata":"https://www.wikidata.org/wiki/Q159190","display_name":"Amplitude","level":2,"score":0.6107000112533569},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5999000072479248},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.5067999958992004},{"id":"https://openalex.org/C168110828","wikidata":"https://www.wikidata.org/wiki/Q1331626","display_name":"Spectral density","level":2,"score":0.4921000003814697},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4772000014781952},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47440001368522644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46320000290870667},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C201080289","wikidata":"https://www.wikidata.org/wiki/Q5156587","display_name":"Complex normal distribution","level":3,"score":0.42750000953674316},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4242999851703644},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.38109999895095825},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.37959998846054077},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.35670000314712524},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C179117685","wikidata":"https://www.wikidata.org/wiki/Q328998","display_name":"Complex plane","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.33090001344680786},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.32739999890327454},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C128963836","wikidata":"https://www.wikidata.org/wiki/Q6322815","display_name":"K-distribution","level":3,"score":0.3001999855041504},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28780001401901245},{"id":"https://openalex.org/C157626765","wikidata":"https://www.wikidata.org/wiki/Q2088081","display_name":"Phase plane","level":3,"score":0.28700000047683716},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.28619998693466187},{"id":"https://openalex.org/C166921843","wikidata":"https://www.wikidata.org/wiki/Q3776487","display_name":"Statistical parameter","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.28119999170303345},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C51267290","wikidata":"https://www.wikidata.org/wiki/Q5527848","display_name":"Gaussian random field","level":4,"score":0.2689000070095062}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.26344","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26344","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.26344","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26344","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7570818066596985,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,127,176],"complex":[1,96,112],"Gaussian":[2,22,97],"distribution":[3,165],"has":[4],"been":[5],"widely":[6,188],"used":[7,189],"as":[8,92],"a":[9,80,93,124,130,135,183],"fundamental":[10],"spectral":[11],"and":[12,18,114,166,179,198],"noise":[13],"model":[14,83,106,128,211],"in":[15,35,72,191,216],"signal":[16,192],"processing":[17],"communication.":[19],"However,":[20],"its":[21,26],"structure":[23,118],"often":[24],"limits":[25],"ability":[27],"to":[28,57,153],"represent":[29],"the":[30,40,68,104,111,116,143,150,159,163,168,172,195,209],"diverse":[31],"amplitude":[32,46,102,174,178],"characteristics":[33],"observed":[34],"individual":[36],"source":[37],"signals.":[38],"On":[39],"other":[41],"hand,":[42],"many":[43],"existing":[44],"non-Gaussian":[45],"distributions":[47,181,190,215],"derived":[48,177],"from":[49,146],"hyperspherical":[50,101],"models":[51],"achieve":[52],"good":[53],"empirical":[54],"fit":[55],"due":[56],"their":[58],"power-law":[59],"structures,":[60],"while":[61,122],"they":[62],"do":[63],"not":[64],"explicitly":[65],"account":[66],"for":[67,84],"complex-plane":[69],"geometry":[70,145],"inherent":[71],"complex-valued":[73,85,120],"observations.":[74],"In":[75],"this":[76],"paper,":[77],"we":[78],"propose":[79],"new":[81],"probabilistic":[82],"random":[86],"variables,":[87],"which":[88],"can":[89],"be":[90],"interpreted":[91],"power-weighted":[94],"noncentral":[95],"distribution.":[98,175],"Unlike":[99],"conventional":[100,214],"models,":[103],"proposed":[105,164,210],"is":[107],"formulated":[108],"directly":[109],"on":[110,203],"plane":[113],"preserves":[115],"geometric":[117],"of":[119,142,155,171,218],"observations":[121],"retaining":[123],"higher-dimensional":[125],"interpretation.":[126],"introduces":[129],"nonlinear":[131],"phase":[132,151],"diffusion":[133,148],"through":[134],"single":[136],"shape":[137],"parameter,":[138],"enabling":[139],"continuous":[140],"control":[141],"distributional":[144],"arc-shaped":[147],"along":[149],"direction":[152],"concentration":[154],"probability":[156],"mass":[157],"toward":[158],"origin.":[160],"We":[161],"formulate":[162],"analyze":[167],"statistical":[169],"properties":[170],"induced":[173],"power":[180,205],"provide":[182],"unified":[184],"framework":[185],"encompassing":[186],"several":[187],"modeling,":[193],"including":[194],"Rice,":[196],"Nakagami,":[197],"gamma":[199],"distributions.":[200],"Experimental":[201],"results":[202],"speech":[204],"spectra":[206],"demonstrate":[207],"that":[208],"consistently":[212],"outperforms":[213],"terms":[217],"log-likelihood.":[219]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-31T00:00:00"}
