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dc.contributor.advisor董槐林
dc.contributor.author李坤森
dc.date.accessioned2018-12-05T01:35:02Z
dc.date.available2018-12-05T01:35:02Z
dc.date.issued2018-01-03
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/169712
dc.description.abstract癫痫是一种危害人类健康的常见病和多发病之一,随时随地地发作给患者身心健康造成很大影响,在很多国家已经成为神经系统很受重视的高发疾病。脑电图是常用于辅助检测癫痫的一种重要手段,但是癫痫患者的脑电图不总是显示异常,所以依靠观察脑电图进行癫痫脑电识别依然存在问题,而且经过研究发现癫痫具有较强的随机性、非平稳性和非线性等特点,对癫痫疾病相关的研究带来较大的困扰。因此如何有效地提取脑电特征来表征癫痫脑电特征的信息,是进行癫痫诊断的首要问题。 针对癫痫脑电信号具有的随机性、非平稳性以及非线性等特点,本文提出了混合特征提取,将时域方法和非线性分析方法混合提取特征,然后采用粒子群优化算法进行优化选择,最后利...
dc.description.abstractEpilepsy is one of the common diseases and frequently-occurring diseases which endangers the health of human beings and gets more attention in many countries. EEG is an important method used to detect the epileptic. However the EEG of epileptics don’t show abnormal all the time, it still exists problem to recognize the epileptic depending on the EEG only. Moreover, researchers have found that the ...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=59076&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=60039
dc.subject癫痫
dc.subject粒子群优化
dc.subjectRBF神经网络
dc.subjectEpilepsy
dc.subjectParticle Swarm Optimization
dc.subjectRBF Neural Network
dc.title基于粒子群的RBF神经网络的癫痫脑电信号分类研究
dc.title.alternativeResearch on Epileptic EEG Signal Classification Based on Particle Swarm Optimization and RBF Neural Network
dc.typethesis
dc.date.replied2017-05-12
dc.description.note学位:工学硕士
dc.description.note院系专业:软件学院_计算机科学与技术
dc.description.note学号:24320141152397


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