Specimen identification techniques employing binary non-linear functions of autocorrelation functions

• 1. 一种运用二进制码组合识别技术的读卡器及其卡片 [P] . 中国专利： CN212724024U . 2021-03-16
• 2. 一种运用二进制码组合识别技术的读卡器及其卡片 [P] . 中国专利： CN112036207A . 2020-12-04
• 3. Specimen identification techniques employing non-linear functions of autocorrelation functions [P] . 美国专利： US3196394A . 1965-07-20

  机译： 使用自相关函数的非线性函数的标本识别技术

• 4. Specimen identification techniques employing selected functions of autocorrelation functions [P] . 美国专利： US3196399A . 1965-07-20

  机译： 使用自相关函数的选定函数的标本识别技术

• 5. Specimen identification techniques employing nth-order autocorrelation functions [P] . 美国专利： US3196397A . 1965-07-20

  机译： 使用n阶自相关函数的标本识别技术

• 1. Binary Sequence Pairs With Two-level Autocorrelation Functions [C] . Y.Takata, T.Torigoe, E.Kobayashi, 2007 international conference on wireless communications, networking and mobile computing . 2007
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• 4. 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
• 5. Generalization of Autocorrelation and Partial Autocorrelation Functions Useful for Identification of ARMA(p,q) Processes [R] . Takemura, A. 1984

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