文献
J-GLOBAL ID:201702250030425921
整理番号:17A1622617
加法的時変遅延コンポーネントを持つニューラルネットワークのための改良された結果への新しいLebesgue積分ベースアプローチ【Powered by NICT】
Novel Lebesgue-integral-based approach to improved results for neural networks with additive time-varying delay components
著者 (7件):
Zeng Deqiang
(Data Recovery Key Laboratory of Sichuan Province, Neijiang Normal University, Neijiang, Sichuan 641100, PR China)
,
Zeng Deqiang
(Numerical Simulation Key Laboratory of Sichuan Province, Neijiang Normal University, Neijiang, Sichuan 641100, PR China)
,
Zhang Ruimei
(School of Mathematics Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China)
,
Zhong Shouming
(School of Mathematics Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China)
,
Yang Guowu
(Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China)
,
Yu Yongbin
(School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, PR China)
,
Shi Kaibo
(School of Information Sciences and Engineering, Chengdu University, Chengdu, Sichuan 610106, PR China)
資料名:
Journal of the Franklin Institute. Engineering and Applied Mathematics
(Journal of the Franklin Institute. Engineering and Applied Mathematics)
巻:
354
号:
16
ページ:
7543-7565
発行年:
2017年
JST資料番号:
C0292A
ISSN:
0016-0032
CODEN:
JFINA
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)