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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/4922
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| タイトル: | Reconstruction of Chaotic Dynamics via a Network of Stochastic Resonance Neurons and Its Application to Speech |
| 著者: | Tokuda, Isao
Yanai, Tomokazu
Aihara, Kazuyuki |
| キーワード: | Stochastic Resonance
Neural Network
Chaos
Speech
Auditory System |
| 発行日: | 2001-03 |
| 出版者: | Springer |
| 誌名: | Artificial Life and Robotics |
| 巻: | 5 |
| 号: | 1 |
| 開始ページ: | 33 |
| 終了ページ: | 39 |
| DOI: | 10.1007/BF02481318 |
| 抄録: | As a new framework for understanding sensory mechanism of biological systems, a great deal of attention has been recently paid to stochastic resonance. The stochastic resonance explains properties of sensory neurons that accurately detect weak input stimuli by using a small amount of internal noise. In particular, Collins et al. reported that a network of stochastic resonance neurons gives rise to robust sensory function for detecting a variety of complex input signals. In this study, we investigate effectiveness of such stochastic resonance neural networks to chaotic input signals. By using the Rossler equations, we analyze the network capability of detecting chaotic dynamics. We also apply the stochastic resonance network systems to speech signals and examine plausibility of the stochastic resonance neural network as a possible model for the human auditory system. |
| Rights: | This is the author-created version of Springer, Isao Tokuda, Tomokazu Yanai and Kazuyuki Aihara, Artificial Life and Robotics, 5(1), 2001, 33-39. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/BF02481318 |
| URI: | http://hdl.handle.net/10119/4922 |
| 資料タイプ: | author |
| 出現コレクション: | b10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
| ファイル |
記述 |
サイズ | 形式 |
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| C6285.pdf | | 249Kb | Adobe PDF | 見る/開く |
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