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Article citations


Khatri, K.L. and Tamil, L. (2017) Early Detection of Peak Demand Days of Chronic Respiratory Diseases Emergency Department Visits Using Artificial Neural Networks. IEEE Journal of Biomedical and Health Informatics, 22, 285-290.

has been cited by the following article:

  • TITLE: Peak Detection Implementation for Real-Time Signal Analysis Based on FPGA

    AUTHORS: Alperen Mustafa Colak, Taito Manabe, Yuichiro Shibata, Fujio Kurokawa

    KEYWORDS: AMPD Algorithm, Off-Line Method, FPGA, Peak Detection

    JOURNAL NAME: Circuits and Systems, Vol.9 No.10, October 31, 2018

    ABSTRACT: In this paper a real-time peak detection method based on modified Automatic Multiscale Field Detection (AMPD) algorithm and Field Programmable Gate Arrays (FPGA) technologies of a time series data is studied, and optimum scaling is highlighted after testing several scales. To validate the results obtained from modified algorithm, they are compared with the results of original AMPD method. As data of this study, three-phase voltage values of a power station are used. A detail detective sensitivity analysis of phase-to-phase voltage values is tried at different scales. Moreover, the original algorithm is tested regarding the off-line mode to obtain optimum scaling for real-time peak point detection. It is concluded that the peak detection of minimum and maximum points of data series achieved by modified algorithm is very close to the results of original AMPD algorithm.