博碩士論文 107323068 完整後設資料紀錄

DC 欄位 語言
DC.contributor機械工程學系zh_TW
DC.creator陳又彰zh_TW
DC.creatorYou-Zhang Chenen_US
dc.date.accessioned2020-8-24T07:39:07Z
dc.date.available2020-8-24T07:39:07Z
dc.date.issued2020
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=107323068
dc.contributor.department機械工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract本論文旨在建構一套盲源分離軟體,並導入深度學習演算法,以此實現音頻擷取時的降噪功能,並於未來應用於智慧製造的領域。 實驗流程方面,本論文先以乾淨的音源訊號進行模型訓練,以此驗證本論文建構之軟體的正確性,再將各式噪音與原始訊號合成,研究應用深 度學習於音頻降噪實現時最佳的模型訓練方式。zh_TW
dc.description.abstractThe propose of the thesis is to build a blind source separation program which based on deep learning algorithm. The goal is to achieve noise reduction while capturing sound signals, and to applicate in intelligent manufacturing in the future. The process of experimentation is training the model with clean audio signal at first. It would verify if the program be written properly. After the verification, the original signal combined with noise would be used to train the model for researching the best training method on noise reduction.en_US
DC.subject深度學習zh_TW
DC.subject盲源分離zh_TW
DC.subjectdeep learningen_US
DC.subjectblind source separationen_US
DC.title應用深度學習於盲源分離之實現zh_TW
dc.language.isozh-TWzh-TW
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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