Online Education and Wireless Network Coordination of Electronic Music Creation and Performance under Artificial Intelligence

Abstract

This paper is aimed at studying the online education and wireless network collaboration on electronic music creation and performance under artificial intelligence (AI). This paper uses a fuzzy clustering algorithm (FCA), designs the sensor network-related equipment, and uses AI to design an electronic music creation system. The analysis of simulation experiments suggests that under the premise of increasing the number of neighbors, the Mean Absolute Error (MAE) and Mean Squared Error (MSE) of collaborative filtering and fuzzy $C$ -means clustering algorithms show a downward trend. However, with the same number of neighbors, the filtering matching algorithm is greater than FCA regarding the mean values of MAE and MSE. Meanwhile, on the electronic music performance system of AI, the digital module is designed and the sound data are imaged on the oscilloscope, and the collaboration of electronic music online education and wireless network is completed. The following conclusion is drawn: modularizing the creative mode of intelligent electronic music has achieved higher computational efficiency. Through the oscilloscope, the sound feature is converted into the image structure, and the corresponding sound and image mode is formed, which realizes the purpose of online electronic music intelligent matching and optimizes the effect of online education. In the AI environment, the matching degree of verification electronic music curriculum resources is better than traditional matching algorithms, and the accuracy is higher.