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Fast algorithms for computing statistics under interval uncertainty, with applications to computer science and to electrical and computer engineering

机译：在区间不确定性下计算统计信息的快速算法，应用于计算机科学以及电气和计算机工程

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作者
Xiang, Gang;
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作者单位

The University of Texas at El Paso;

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授予单位 The University of Texas at El Paso;
学科
学位 Ph.D.
年度 2007
页码 159 p.
总页数 159
原文格式 PDF
正文语种 eng
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1. Session "Interval and Computer-Algebraic Methods in Science and Engineering" At the 6th International Association for Mathematics and Computers in Simulation (IMACS) Conference of Applications of Computer Algebra (ACA'2000) [J] . Vyacheslav Nesterov, Vladik Kreinovich Reliable Computing . 2001,第1期

机译：在第六届国际数学与模拟计算机协会（IMACS）计算机代数应用会议（ACA'2000）上的会议“科学与工程中的间隔和计算机代数方法”
2. Towards Combining Probabilistic and Interval Uncertainty in Engineering Calculations: Algorithms for Computing Statistics under Interval Uncertainty, and Their Computational Complexity [J] . VLADIK KREINOVICH, GANG XIANG, SCOTT A. STARKS, Reliable Computing . 2006,第6期

机译：在工程计算中将概率和区间不确定性相结合：区间不确定性下的统计计算算法及其计算复杂性
3. SCAN 2000 GAMM-IMACS International Symposium on Scientific Computing, Computer Arithmetic, and Validated Numerics Interval 2000: International Conference on Interval Methods in Science and Engineering [J] . Axel Facius, Rudolf Lohner Reliable Computing . 2001,第2期

机译：SCAN 2000 GAMM-IMACS 2000年科学计算，计算机算术和有效数字间隔国际研讨会：科学和工程学间隔方法国际会议
4. Evaluation of the Adaptive Statistical Iterative Reconstruction Algorithm in Chest CT (Computed Tomography) - A Preliminary Study toward Its Employment in Low Dose Applications, Also in Conjunction with CAD (Computer Aided Detection) [C] . Patrizio Barca, Federica Palmas, Maria Evelina Fantacci, International Joint Conference on Biomedical Engineering Systems and Technologies . 2018

机译：评估胸部CT（计算机断层扫描）的自适应统计迭代重建算法 - 对低剂量应用中的就业初步研究，以及CAD（计算机辅助检测）
5. Fast parallel algorithms on a class of graph structures with applications in relational databases and computer networks [D] . Radhakrishnan, Sridhar 1990

机译：一类图结构上的快速并行算法及其在关系数据库和计算机网络中的应用
6. Computer Applications in Medical Care. Computers in Nursing. Nursing Practice Applications: The Comparative Utility of a File Cabinet Program vs a General Statistical Program in Micro-Computer Management and Analysis of Clinical Nursing Data [O] . Patricia M. Schwirian 1983

机译：医疗保健中的计算机应用。护理中的计算机。护理实践应用：文件柜程序与一般统计程序在微计算机管理和临床护理数据分析中的比较实用性
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）
8. Federal Coordinating Council on Science, Engineering and Technology, Committee on Computer Research and Applications, Subcommittee on Science and Engineering Computing: Annual Report, 1987. [R] . 1988

机译：联邦科学，工程和技术协调委员会，计算机研究和应用委员会，科学和工程计算小组委员会：1987年年度报告。

Fast algorithms for computing statistics under interval uncertainty, with applications to computer science and to electrical and computer engineering

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