New Electrical Engineering Research Has Been Reported by Scientists at Pennsylvania State University

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New Electrical Engineering Research Has Been Reported by Scientists at Pennsylvania State University

机译：宾夕法尼亚州立大学的科学家报道了新的电气工程研究

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2011 FEB 2 - (VerticalNews.com) -- New investigation results, 'An empiricalrnmethod to estimate the viscosity of mineral oil by means of ultrasonic attenuation,' are detailedrnin a study published in Ieee Transactions On Ultrasonics, Ferroelectrics, and FrequencyrnControl. "This paper presents an empirical method for measuring the viscosity of mineral oil. Inrna built-in pipeline application, conventional ultrasonic methods using shear reflectance orrnrheological and acoustical phenomena may fail because of attenuated shear wave propagationrnand an unpredictable spreading loss caused by protective housings and comparable mainrnflows," investigators in the United States report.

机译：2011年2月2日-（VerticalNews.com）-Ieee Transactions on Ultrasonics，Ferroelectrics和FrequencyrnControl发表的一项研究详细介绍了新的调查结果“一种通过超声衰减估算矿物油粘度的经验方法”。 “本文提出了一种测量矿物油粘度的经验方法。Inrna内置管道应用，使用剪切反射率或流变学和声学现象的常规超声方法可能会因剪切波传播衰减和保护罩引起的不可预测的传播损失而失效。 mainrnflows”，美国调查人员报告。

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《Energy Business Journal》 |2011年第31期|48-48|共1页
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City:University Park; State:PA; Country:United States; Electrical Engineering; Electronics; Mathematics; Polynomial; Wave Propagation;

机译：城市：大学公园;州：PA;国家：美国;电气工程;电子产品;数学;多项式波浪传播;

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7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

New Electrical Engineering Research Has Been Reported by Scientists at Pennsylvania State University

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