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作品数:2536被引量:5264H指数:25
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相关作者:王霓陆平秦玲娣李雪峰刘雪松更多>>
相关机构:东南大学复旦大学中山大学中国科学院更多>>
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相关基金:国家自然科学基金国家重点基础研究发展计划国家高技术研究发展计划中国博士后科学基金更多>>
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Comparison of signal reconstruction under different transforms
《Journal of Southeast University(English Edition)》2015年第4期474-478,共5页刘洁媛 伍家松 Lotfi Senhadji 舒华忠 
The National Natural Science Foundation of China(No.61201344;61271312;11301074);the Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092110023;20120092120036);the Program for Special Talents in Six Fields of Jiangsu Province(No.DZXX-031);the Natural Science Foundation of Jiangsu Province(No.BK2012329;BK2012743);the United Creative Foundation of Jiangsu Province(No.BY2014127-11);the"333"Project(No.BRA2015288)
A newalgorithm, called Magnitude Cut, to recover a signal from its phase in the transform domain, is proposed.First, the recovery problem is converted to an equivalent convex optimization problem, and then it is solve...
关键词:MagnitudeCut algorithm signal reconstruction different transforms convex optimization phase information 
Comparison of dispersion of nanoparticles ultrasonicated with probe and cup horn
《Journal of Southeast University(English Edition)》2011年第4期441-444,共4页张小强 尹立红 浦跃朴 
The National Basic Research Program of China(No.2011CB933404);the Foundation of Jiangsu Key Laboratory for Biomaterials and Devices(No.2010LBMD05)
This study aims to investigate the effects of a probe and a cup horn on the de-agglomeration efficiency in ultrasound vibration processes. TiO2 and Al2O3 nanoparticle dispersions were prepared in distilled water at a ...
关键词:NANOPARTICLES DISPERSION ultrasonic devices 
A prediction comparison between univariate and multivariate chaotic time series被引量:3
《Journal of Southeast University(English Edition)》2003年第4期414-417,共4页王海燕 朱梅 
The methods to determine time delays and embedding dimensions in the phase space delay reconstruction of multivariate chaotic time series are proposed. Three nonlinear prediction methods of multivariate chaotic tim...
关键词:multivariate chaotic time series phase space reconstruction PREDICTION neural networks 
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