{
    "article_id": 605,
    "public_id": "99f0d05a-cb24-42bd-915f-21e08cdfeee0",
    "internal_identifier": null,
    "source_identifier": "5:255",
    "status": "published",
    "type": "research_article",
    "title": "Negatif Olmayan Matris Ayrıştırma ile Tek Kanal Kör Kaynak Ayrıştırma",
    "title_secondary": null,
    "abstract": "Kör kaynak ayrıştırma, birden fazla sinyalin karışımını içeren bir veri kümesinden bu karışımı oluşturan her bir kaynağın tahmin edilmesi olarak tanımlanabilir. Bu işlemin kör olarak adlandırılması kaynaklar hakkında hiçbir ek bilgi olmadığını belirtmektedir. Kör kaynak ayrıştırma da tahmin edilecek sinyal sayısı kadar karışım sinyali varken, tek kanal kör kaynak ayrıştırma işleminde sadece bir karışım sinyali olduğundan kaynakların tahmini maliyetli bir işlemdir. Bahsedilen bu yöntemle herhangi bir işarete eklenmiş istenmeyen bir gürültü, bozucu bir etki veya başka bir sinyal kaynağı diğer bir kaynaktan\r\nayrıştırılabilir veya bu çalışmada olduğu gibi tek bir mikrofonla kaydedilmiş 2 farklı enstrümantal işaret kaynağı birbirinden ayrıştırılabilir. Yapılan bu çalışmada sürekli dalgacık dönüşümü kullanılarak negatif olmayan matris ayrıştırma ile tek kanallı olarak kaydedilen iki işaret birbirinden ayrıştırılmıştır. Önerilen yöntemin başarım analizini değerlendirmek için sonuçlar işaret gürültü oranı cinsinden değerlendirilmiştir.  ",
    "language": "tr",
    "english_title": "Single-Channel Blind Source Decomposition with Non-Negative Matrix Decomposition",
    "english_abstract": "Blind source decomposition can be defined as the estimation of each source that makes up a mixture from a dataset containing a mixture of multiple signals. The term \"blind\" indicates that there is no additional information about the sources. While blind source decomposition involves as many mixed signals as there are signals to be estimated, single-channel blind source decomposition only involves one mixed signal, making source estimation a costly process. This method can separate unwanted noise, interference, or other signal sources added to any signal from another source, or, as in this study, separate two different instrumental signal sources recorded with a single microphone. In this study, two signals recorded in a single channel were separated using non-negative matrix decomposition with continuous wavelet transform. To evaluate the performance analysis of the proposed method, the results were evaluated in terms of signal-to-noise ratio.",
    "doi": null,
    "doi_url": null,
    "resource_url": "https://www.set-science.com/a/99f0d05a-cb24-42bd-915f-21e08cdfeee0",
    "pdf_url": "https://www.set-science.com/a/99f0d05a-cb24-42bd-915f-21e08cdfeee0/pdf",
    "og_image": "https://www.set-science.com/assets/img/og-card-v2.png",
    "authors": [
        {
            "public_id": "08eb3857-8290-42e0-bbf3-464203ae6e2d",
            "given": "Hüsamettin",
            "family": "Çelik",
            "full": "Hüsamettin Çelik",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "fyilgzin@erzincan.edu.tr",
            "corresponding": false,
            "sequence": "first",
            "affiliations": [
                {
                    "name": "Erzincan University",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        },
        {
            "public_id": "b5758bac-819a-4b09-9f0e-2090860acfc3",
            "given": "Fatih Yavuz",
            "family": "Ilgın",
            "full": "Fatih Yavuz Ilgın",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "fyilgin@erzincan.edu.tr",
            "corresponding": true,
            "sequence": "additional",
            "affiliations": [
                {
                    "name": "Erzincan University",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        },
        {
            "public_id": "ada2da54-5587-42c3-acfa-f79db9567e08",
            "given": "Yusuf",
            "family": "Sevim",
            "full": "Yusuf Sevim",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "fyilxgin@erzincan.edu.tr",
            "corresponding": false,
            "sequence": "additional",
            "affiliations": [
                {
                    "name": "Karadeniz Technical University",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        }
    ],
    "keywords": [],
    "translations": [
        {
            "language": "en",
            "title": "Single-Channel Blind Source Decomposition with Non-Negative Matrix Decomposition",
            "abstract": "Blind source decomposition can be defined as the estimation of each source that makes up a mixture from a dataset containing a mixture of multiple signals. The term \"blind\" indicates that there is no additional information about the sources. While blind source decomposition involves as many mixed signals as there are signals to be estimated, single-channel blind source decomposition only involves one mixed signal, making source estimation a costly process. This method can separate unwanted noise, interference, or other signal sources added to any signal from another source, or, as in this study, separate two different instrumental signal sources recorded with a single microphone. In this study, two signals recorded in a single channel were separated using non-negative matrix decomposition with continuous wavelet transform. To evaluate the performance analysis of the proposed method, the results were evaluated in terms of signal-to-noise ratio.",
            "keywords": [
                "Kör Kaynak Ayrıştırma, Kokteyl Parti Problemi, Negatif Olmayan Matris Ayrıştırma, Sürekli Dalgacık Dönüşümü"
            ]
        }
    ],
    "subjects": [],
    "subject_names": [],
    "published_date": "2018-06-23",
    "published_year": "2018",
    "received_date": null,
    "accepted_date": null,
    "volume": "2",
    "issue": null,
    "page_first": "387",
    "page_last": "387",
    "article_number": null,
    "conference": {
        "short_name": "ISAS 2018",
        "full_title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "name": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "acronym": "ISAS 2018",
        "location": "Kemer-Antalya, Türkiye",
        "start_date": "2018-04-11",
        "end_date": null,
        "public_id": "1d94fec9-c4fe-4034-9157-0b205eef4e56"
    },
    "proceedings": {
        "title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "series_title": "Setsci conference indexing system",
        "publisher": "SET Technology",
        "isbn": null,
        "eisbn": null,
        "issn": "2618-6446",
        "eissn": null,
        "doi": null,
        "doi_prefix": null,
        "slug": "setsci-volume-2-2018-legacy-5",
        "public_id": "03da7b1c-cb6e-4f3b-aee4-ac41ee60fd75",
        "url": "https://www.set-science.com/p/setsci-volume-2-2018-legacy-5"
    },
    "license": {
        "name": "CC BY 4.0",
        "url": "https://creativecommons.org/licenses/by/4.0/",
        "code": "CC-BY-4.0",
        "open_access": true
    },
    "copyright": {
        "holder": "SET Technology",
        "year": "2018"
    },
    "funding_statement": null,
    "funders": [],
    "references": [],
    "statements": {
        "acknowledgements": null,
        "conflict_of_interest": null,
        "data_availability": null,
        "ai_disclosure": null
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    "credit": [],
    "history": {
        "published": "2018-06-23"
    }
}