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J-GLOBAL ID：201902259588260908   Reference number：19A2402009

Quantitative Analysis of Dynamical Complexity in Cultured Neuronal Network Models for Reservoir Computing Applications

貯水池計算応用のための培養神経回路網モデルにおける動的複雑性の定量分析【JST・京大機械翻訳】

Author (5)： Moriya Satoshi (Research Institute of Electrical Communication, Tohoku University, Sendai, Miyagi, Japan) ,  Yamamoto Hideaki (WPI-Advanced Institute for Materials Research, Tohoku University, Sendai, Miyagi, Japan) ,  Hirano-Iwata Ayumi (WPI-Advanced Institute for Materials Research, Tohoku University, Sendai, Miyagi, Japan) ,  Kubota Shigeru (Graduate School of Science and Engineering, Yamagata University, Yonezawa, Yamagata, Japan) ,  Sato Shigeo (Research Institute of Electrical Communication, Tohoku University, Sendai, Miyagi, Japan)
Material： IEEE Conference Proceedings  (IEEE Conf Proc)
Volume： 2019  Issue： IJCNN  Page： 1-6  Publication year： 2019 
JST Material Number： W2441A  Document type： Proceedings
Article type： 原著論文  Country of issue： United States (USA)  Language： ENGLISH (EN)

Abstract/Point： Reservoir computing is a machi...

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Thesaurus term： cortex ,  burst ,  Machine Learning ,  *reservoir (water) ,  computer system (hardware) ,  excitation (physiology) ,  measure ,  connectivity ,  coherence ,  *culture (biology) ,  network ,  neuron ,  *Nerve ,  *complexity
Semi thesaurus term： 貯留層 , 【Automatic Indexing@JST】

JST classification (3)： Graphic and image processing in general  (JE04010I) ,  Biometry  (EL03020C) ,  Pattern recognition  (JE07000S)

Terms in the title (7)： 貯水池 ,  計算 ,  応用 ,  培養 ,  神経回路網モデル ,  複雑性 ,  定量分析