Power scheduling for distributed multiple-hypothesis detection by task-specific information
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, H.-S. | - |
dc.contributor.author | Yang, S.-I. | - |
dc.date.accessioned | 2021-06-22T20:43:27Z | - |
dc.date.available | 2021-06-22T20:43:27Z | - |
dc.date.created | 2021-05-11 | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/19275 | - |
dc.description.abstract | We introduce a new information theoretic power allocation scheme applicable to distributed multiple-hypothesis detection systems communicating over slow fading channels. In earlier work, it was demonstrated that performance could be improved by adjusting transmit power to maximize the J-divergence measure of a binary detection system and the J-divergence method is extended for a distributed multiple-hypothesis detection system by defining pairwise sums of the J-divergences. However, the pairwise sum measure does not provide a tight bound. Basically, the more hypotheses we adopt, the less efficient the optimization is. Thus, we derive a more efficient classification-oriented information measure for power optimization of distributed multiple-hypothesis system by introducing a virtual decider variable. The virtual decider variable is directly related with classification task. Various numerical results are also shown to compare the performances. ? 2015 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Power scheduling for distributed multiple-hypothesis detection by task-specific information | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Yang, S.-I. | - |
dc.identifier.doi | 10.1109/ICSPCC.2015.7338862 | - |
dc.identifier.scopusid | 2-s2.0-84960976569 | - |
dc.identifier.bibliographicCitation | 2015 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2015 | - |
dc.relation.isPartOf | 2015 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2015 | - |
dc.citation.title | 2015 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2015 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Classification (of information) | - |
dc.subject.keywordPlus | Fading channels | - |
dc.subject.keywordPlus | Information theory | - |
dc.subject.keywordPlus | Rayleigh fading | - |
dc.subject.keywordPlus | Signal detection | - |
dc.subject.keywordPlus | Signal processing | - |
dc.subject.keywordPlus | Distributed classification | - |
dc.subject.keywordPlus | Distributed detection | - |
dc.subject.keywordPlus | Multiple hypothesis | - |
dc.subject.keywordPlus | Mutual informations | - |
dc.subject.keywordPlus | Optimal power allocation | - |
dc.subject.keywordPlus | Slow fading | - |
dc.subject.keywordPlus | Specific information | - |
dc.subject.keywordPlus | Electric power system measurement | - |
dc.subject.keywordAuthor | classification | - |
dc.subject.keywordAuthor | distributed classification | - |
dc.subject.keywordAuthor | distributed detection | - |
dc.subject.keywordAuthor | multiple hypotheses | - |
dc.subject.keywordAuthor | mutual information | - |
dc.subject.keywordAuthor | optimal power allocation | - |
dc.subject.keywordAuthor | Rayleigh fading channel | - |
dc.subject.keywordAuthor | slow fading | - |
dc.subject.keywordAuthor | task-specific information | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/7338862 | - |
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