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Auditory Pulse Neural Network Model to Extract the Inter-Aural Time and Level Difference for Sound Localization
https://nitech.repo.nii.ac.jp/records/4280
https://nitech.repo.nii.ac.jp/records/42804cf79ab5-cd03-4e25-bd16-bd2cef4115eb
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
本文_fulltext (804.9 kB)
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Copyright(c)1994 IEICE http://search.ieice.org/index.html
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||||||
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| 公開日 | 2012-11-07 | |||||||||
| タイトル | ||||||||||
| タイトル | Auditory Pulse Neural Network Model to Extract the Inter-Aural Time and Level Difference for Sound Localization | |||||||||
| 言語 | en | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者 |
Kuroyanagi, Susumu
× Kuroyanagi, Susumu
× Iwata, Akira
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| 著者別名 | ||||||||||
| 姓名 | 黒柳, 奨 | |||||||||
| 著者別名 | ||||||||||
| 姓名 | 岩田, 彰 | |||||||||
| bibliographic_information |
en : IEICE transactions on information and systems 巻 E77-D, 号 4, p. 466-474, 発行日 1994-04-20 |
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| 出版者 | ||||||||||
| 出版者 | Institute of Electronics, Information and Communication Engineers | |||||||||
| 言語 | en | |||||||||
| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 0916-8532 | |||||||||
| item_10001_source_id_32 | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AA10826272 | |||||||||
| 出版タイプ | ||||||||||
| 出版タイプ | VoR | |||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||
| 内容記述 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | A novel pulse neural network model for sound localization has been proposed. Our model is based on the physiological auditory nervous system. Human beings can perceive the sound direction using inter-aural time difference (ILD) and inter-aural level difference (ILD) of two sounds. The model extracts these features using only pulse train information. The model is divided roughly into three sections: preprocessing for input signals; transforming continuous signals to pulse trains; and extracting features. The last section consists of two parts: ITD extractor and ILD extractor. Both extractors are implemented using a pulse neuron model. They have the same network structure, differing only in terms of parameters and arrangements of the pulse neuron model. The pulse neuron model receives pulse trains and outputs a pulse train. Because the pulses have only simple informations, their data structures are very simple and clear. Thus, a strict design is not required for the implementation of the model. These advantages are profitable for realizing this model by hardware. A computer simulation has demonstrated that time and level differences between two signals have been successfully extracted by the model. | |||||||||
| 言語 | en | |||||||||
