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Issue title: Special Section: Applied Machine Learning and Management of Volatility, Uncertainty, Complexity & Ambiguity (V.U.C.A)
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Haiyan, Zhanga; * | Bo, Zhengb | Haojun, Zuc
Affiliations: [a] Northeast Normal University, Institute of International and Comparative Education, Faculty of Education, Changchun, Jilin, China | [b] Hebei Normal University of Science and Technology, Hebei, China | [c] Ukovsky State Normal University South Ukraine, Odessa, Ukraine
Correspondence: [*] Corresponding author. Haiyan Zhang, Northeast Normal University, Institute of International and Comparative Education, Faculty of Education, Changchun, Jilin 130024, China. E-mail: wei2019ps@163.com.
Abstract: The current music education information has certain information loss in the real-time transmission process, which leads to poor educational effect. The research content of this thesis is based on FPGA video image acquisition and processing system. At the same time, this research mainly uses FPGA as the platform to realize and simulate video acquisition, transformation, storage, display and transmission. This research solves the problem of long-distance real-time transmission of high-definition video stream, and in order to improve the subjective quality of the recovered video at the receiving end, the algorithm processing is added to reduce the blockiness phenomenon in the video displayed at the receiving end. Finally, the validation test was designed to validate the research perspective. The experimental results show that the system works stably and realizes the functions of video image acquisition, conversion, display and transmission, and achieves the design goal. However, due to time constraints and other conditions, the entire design needs further improvement, so that it can provide a basis for the development of subsequent music education information communication technology.
Keywords: SVGA video, real-time communication technology, music education information, feature extraction
DOI: 10.3233/JIFS-179947
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1733-1744, 2020
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