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[{"key": "dc.contributor.advisor", "value": "Lehto, Martti", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "P\u00f6l\u00f6nen, Ilkka", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Colliander, Jeremias", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2022-06-01T08:29:11Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2022-06-01T08:29:11Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2022", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/81397", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Teko\u00e4ly on kehittynyt viime vuosina huimaa tahtia ja sit\u00e4 on alettu soveltaa uusien haasteiden ratkaisemiseksi. Yksi t\u00e4llainen haaste on pitk\u00e4\u00e4n ollut useiden radiosignaalien luokittelu toisistaan riitt\u00e4v\u00e4ll\u00e4 tarkkuudella. Tehokkaalla radiosignaalien luokittelulla pysytt\u00e4isiin valvomaan alati kasvavaa radioliikennett\u00e4 sek\u00e4 saamaan suurempi hy\u00f6ty irti rajallisesta radiotaajuusspektrist\u00e4. Aikaisemmat tutkimukset ovat luokitelleet radiosignaaleita k\u00e4ytt\u00e4m\u00e4ll\u00e4 keinotekoisesti luotua aineistoa, joka ei t\u00e4ysin vastaa oikean maailman haasteita ja ongelmia. T\u00e4m\u00e4n tutkimuksen tarkoitus on ker\u00e4t\u00e4 oikeista signaaleista koostuva aineisto sek\u00e4 rakentaa toimiva signaaleiden luokittelija syv\u00e4oppimista (Deep Learning, DL) sek\u00e4 hybridikuvia hy\u00f6dynt\u00e4m\u00e4ll\u00e4. Lis\u00e4ksi tutkimuksessa tutkitaan tavallisen ohjelmistokehityksen sek\u00e4 teko\u00e4lyn kehityksen eroavaisuuksia. Tutkimus tehtiin Jyv\u00e4skyl\u00e4ss\u00e4 toimipistett\u00e4\u00e4n pit\u00e4v\u00e4lle yritys X:lle, jotka tarjosivat keinot signaalien tallentamiseen sek\u00e4 resurssit mallien kouluttamiseen ja signaalien k\u00e4sittelyyn. Tutkimustuloksista k\u00e4vi ilmi, ett\u00e4 radiosignaaleita on mahdollista luokitella hyvinkin tarkasti neuroverkkojen ja hybridikuvien avulla. Tutkimuksesta selvisi my\u00f6s uusia haasteita, joita ei ollut otettu aikaisemmissa tutkimuksissa huomioon. Lis\u00e4ksi selvisi, ett\u00e4 ohjelmistokehitys ja teko\u00e4lyn kehitys eroavat toisistaan huomattavasti, jotka saattavat vaikuttaa suuresti AI projektien onnistumiseen. Toimiva ja skaalautuva malli tarvitsee itselleen paljon tukij\u00e4rjestelmi\u00e4 ja ohjelmia, jotta lopputuloksesta tulee helpommin yll\u00e4pidett\u00e4v\u00e4 ja k\u00e4ytett\u00e4v\u00e4 kokonaisuus.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Artificial intelligence has developed at a rapid pace in recent years and has begun to be applied to meet new challenges. One such challenge has long been the classification of several radio signals with sufficient accuracy. Efficient classification of radio signals would make tracking and controlling of the ever-increasing radio traffic and make greater use of the limited radio frequency spectrum. Previous studies have classified radio signals using artificially generated data that does not fully meet the challenges and problems of the real world. The purpose of this study is to collect data consisting of real signals and to build a working signal classifier using deep learning and hybrid images. In addition, the study examines the differences between ordinary software development and the development of artificial intelligence. The study was carried out for Company X, which has an office in Jyv\u00e4skyl\u00e4. The Company X provided the means to record signals and resources for model training and signal processing. The results of the study showed that it is possible to classify radio signals very accurately using neural networks and hybrid images. The study also revealed new challenges that had not been addressed in the previous studies. In addition, it became clear that software development and the development of artificial intelligence differ significantly, and it may be a key factor in success of AI projects. A functional and scalable model needs a lot of support systems and programs to make the solution easier to maintain and use.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Miia Hakanen (mihakane@jyu.fi) on 2022-06-01T08:29:11Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2022-06-01T08:29:11Z (GMT). No. of bitstreams: 0\n Previous issue date: 2022", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "58", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "fin", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "radiosignaalit", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "luokittelu", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Radiosignaalien tunnistaminen neuroverkon avulla", "language": "", 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"language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Information Technology", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Tietoj\u00e4rjestelm\u00e4tiede", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Information Systems Science", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.collaborator", "value": "business", "language": "", 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