完整後設資料紀錄
DC 欄位語言
dc.contributor.authorUeng, FBen_US
dc.contributor.authorSu, YTen_US
dc.date.accessioned2019-04-02T05:59:53Z-
dc.date.available2019-04-02T05:59:53Z-
dc.date.issued1997-05-01en_US
dc.identifier.issn0253-3839en_US
dc.identifier.urihttp://dx.doi.org/10.1080/02533839.1997.9741828en_US
dc.identifier.urihttp://hdl.handle.net/11536/149550-
dc.description.abstractThe use of second-order statistics in identification or deconvolution incurs error due to additive Gaussian noise. In contrast, higher-order statistics (HOS) are insensitive to Gaussian perturbation and can be used to characterize nonminimum phase (NMP) systems. In this paper we propose batch, recursive and adaptive form algorithms based on third- and fourth-order cumulants to solve the identification and deconvolution problems. A new order determination procedure is also presented. Simulation results demonstrate that our algorithms do have superior performance when compared with existing algorithms.en_US
dc.language.isoen_USen_US
dc.subjectidentificationen_US
dc.subjectdeconvolutionen_US
dc.subjecthigher-order statisticsen_US
dc.titleBlind identification and deconvolution algorithms using higher-order cumulantsen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/02533839.1997.9741828en_US
dc.identifier.journalJOURNAL OF THE CHINESE INSTITUTE OF ENGINEERSen_US
dc.citation.volume20en_US
dc.citation.spage247en_US
dc.citation.epage255en_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.identifier.wosnumberWOS:A1997XF35200002en_US
dc.citation.woscount0en_US
顯示於類別:期刊論文