device for monitoring the correct order of succession of groups of signals of code in plant of electric communication engineering

• 1. 网络节点、第一通信设备及其中用于在不同时长的监视时间段中监视信息信号的方法 [P] . 中国专利： CN110476467A . 2019-11-19
• 2. 用于控制从一组中间金属制品中制造一组最终金属制品的方法和电子设备、相关的计算机程序、制造方法和装置 [P] . 中国专利： CN113316747A . 2021-08-27
• 3. A method for monitoring the correct sequence of code signal groups in devices of the communications [P] . 德国专利： DE2518588C3 . 1978-07-20

  机译： 一种监视通信设备中代码信号组正确序列的方法

• 4. A method for monitoring the correct sequence of code signal groups in devices of the communications [P] . 德国专利： DE2518588B2 . 1977-12-01

  机译： 一种监视通信设备中代码信号组正确序列的方法

• 5. A method for monitoring the correct sequence of code signal groups in devices of the communications [P] . 德国专利： DE2518588A1 . 1976-10-28

  机译： 一种监视通信设备中代码信号组正确序列的方法

• 1. Real-Time Frequency Estimation of Complex GMSI Signal of Green Communications Devices [J] . Umar Suleiman Dauda, NikNoordini NikAbdMalik, Mazlina Esa, 电子科技学刊：英文版 . 2016,第002期
• 2. Randomness of physiological signals in generation cryptographic key for secure communication between implantable medical devices inside the body and the outside world [C] . Hassan Chizari, Emil Lupu, Paula Thomas Living in the Internet of Things: Cybersecurity of the IoT - 2018 . 2018
• 3. Graph-Based Error Correcting Codes for Modern Dense Storage Devices [D] . Hareedy, Ahmed Hassan Mahmoud E. 2018
• 4. Feasibility of Backscatter Communication Using LoRAWAN Signals for Deep Implanted Devices and Wearable Applications [O] . Marc Lazaro, Antonio Lazaro, Ramon Villarino 2020
• 5. 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
• 6. Phase I: the Pipeline-Gas Demonstration Plant. Demonstration Plant Engineering and Design. Volume 22. Plant Section 4000 - Electrical and Communications. [R] . 1981

• 1. Real-Time Frequency Estimation of Complex GMSK Signal of Green Communications Devices [J] . Umar Suleiman Dauda ,NikNoordini NikAbdMalik ,Mazlina Esa . 电子科技学刊 . 2016,第002期
• 2. Monitoring the Technical Condition of Dams of Hydroelectric Power Plants with an Automated Monitoring and Earthquake Registration System [J] . Alexander Kuzmenko ,Daria Korolenko ,Evgeniy Zolotukhin . 能源与动力工程 . 2014,第008期
• 3. Reliable Wireless Communication for Medical Devices Using Turbo Convolution Code [J] . Debasish Bera ,Tapas Chakravarty ,Saswat Chakrabarti . 通讯、网络与系统学国际期刊（英文） . 2010,第8期
• 4. Energy-Constrained Duty-Cycle Optimization for Wireless Implanted Communication Devices [J] . Zhao Xu ,Ye Li . 远程医疗系统和网络（英文） . 2012,第1期
• 5. 基于Lon Works的铁路车站信号设备监视系统 [C] . 李哲英 ,李晓光 . 全国控制网络会议 . 1999
• 6. 第一组代谢型谷氨酸受体在外周痛信号产生中的作用 [A] . 王桢 . 2003