A Low-Energy Application Specific Instruction-Set Processor towards a Low-Computational Lossless Compression Method for Stimuli Position Data of Artificial Vision Systems

• Item type: Journal(1)
• 公開日: 2017-02-15
• タイトル: A Low-Energy Application Specific Instruction-Set Processor towards a Low-Computational Lossless Compression Method for Stimuli Position Data of Artificial Vision Systems
• タイトル / 言語: en
• タイトル: A Low-Energy Application Specific Instruction-Set Processor towards a Low-Computational Lossless Compression Method for Stimuli Position Data of Artificial Vision Systems
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：組込みシステム工学] application-domain specific instruction-set processor, lossless data compression, exponential Golomb coding, entropy coding, cortical visual prosthesis, artificial vision system, low-energy consumption, implantable embedded system
• 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
• 著者所属: Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University
• 著者所属: Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University／The Global Center for Medical Engineering and Informatics, Osaka University
• 著者所属: Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University
• 著者所属: Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University／The Global Center for Medical Engineering and Informatics, Osaka University
• 著者所属(英): en
• 著者所属(英): Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University
• 著者所属(英): en
• 著者所属(英): Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University / The Global Center for Medical Engineering and Informatics, Osaka University
• 著者所属(英): en
• 著者所属(英): Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University
• 著者所属(英): en
• 著者所属(英): Department of Information System Engineering, Graduate School of Information Science and Technology, Osaka University / The Global Center for Medical Engineering and Informatics, Osaka University
• 著者名: Tomoki, Sugiura; Masaharu, Imai; Jaehoon, Yu; Yoshinori, Takeuchi
• 著者名(英): Tomoki, Sugiura; Masaharu, Imai; Jaehoon, Yu; Yoshinori, Takeuchi
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This paper proposes a novel data compression method for artificial vision systems and its low-energy implementation in order to reduce energy consumption in a wireless communication subsystem. The artificial vision systems are one of the methods for realizing visual prosthesis by controlling stimulus to visual nerves, and they consist of an inner stimulating unit and an outer image processing unit. The outer unit transmits information regarding stimulation to the inner unit via wireless communication, which occupies a large portion of the whole energy consumption. Reducing traffic in wireless communication is important to prevent damage caused by extra heat dissipation of the inner unit, which leads to excess energy consumption. The proposed compression method marks a higher compression ratio than the conventional compression methods by taking advantage of the analyses of stimuli position data, which is dominant in traffic. The proposed method is implemented as an application-domain specific instruction-set processor to achieve both configurability of stimulation control and compression efficiency. The evaluation results show that the proposed implementation reduces energy consumption by about 87% and 62% in the compression and decompression process, respectively. These results indicate that the proposed method can expect to reduce energy consumption in a wireless communication receiver dramatically.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.25(2017) (online); DOI http://dx.doi.org/10.2197/ipsjjip.25.210; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This paper proposes a novel data compression method for artificial vision systems and its low-energy implementation in order to reduce energy consumption in a wireless communication subsystem. The artificial vision systems are one of the methods for realizing visual prosthesis by controlling stimulus to visual nerves, and they consist of an inner stimulating unit and an outer image processing unit. The outer unit transmits information regarding stimulation to the inner unit via wireless communication, which occupies a large portion of the whole energy consumption. Reducing traffic in wireless communication is important to prevent damage caused by extra heat dissipation of the inner unit, which leads to excess energy consumption. The proposed compression method marks a higher compression ratio than the conventional compression methods by taking advantage of the analyses of stimuli position data, which is dominant in traffic. The proposed method is implemented as an application-domain specific instruction-set processor to achieve both configurability of stimulation control and compression efficiency. The evaluation results show that the proposed implementation reduces energy consumption by about 87% and 62% in the compression and decompression process, respectively. These results indicate that the proposed method can expect to reduce energy consumption in a wireless communication receiver dramatically.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.25(2017) (online); DOI http://dx.doi.org/10.2197/ipsjjip.25.210; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 58, 号 2, 発行日 2017-02-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764