Abstract
Music pattern description and model establishment are the research hotspots of music cognition and computing musicology. The purpose of this paper is to propose a music fuzzy perception computing model based on fuzzy sets and perceptual learning. Firstly, according to the inversion principle of relational mapping, human music cognition is regarded as the neural network of memory mapping and perception inversion (MMPI), and a conceptual model is established for description. Secondly, based on the analysis of music fuzzy perception characteristics, the fuzzy perceptual feature index (FPCI) of music elements is defined. Finally, a music cognitive learning model based on fuzzy perception features is proposed. Research shows that human music cognition is a learning process based on fuzzy perception, which is a fusion process between music memory and reality cognition. The principle of testing this fusion is to optimize the fuzzy perception of the music.
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Acknowledgements
This paper is supported by the Liaoning Education Science Planning Fund (JG18DB290). In the process of experimental analysis, we got the help of the teachers and students of Liaoning Normal University and Dalian Qimeng Music School. The experimental data in this paper was provided by Wang Xin and Zhang Jiahui. Thank you very much for their help.
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He, Y., He, P. (2020). Computing Model of Musical Multiple Perception Based on Memory Mapping Perception Inversion. In: Jain, V., Patnaik, S., Popențiu Vlădicescu, F., Sethi, I. (eds) Recent Trends in Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-9406-5_13
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DOI: https://doi.org/10.1007/978-981-13-9406-5_13
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