TY -的A2 - Chen Miaochao盟,龚Tianzhuo盟——太阳,sib PY - 2021 DA - 2021/10/22 TI -基于自适应特征提取的音乐信号波动方程反演SP - 8678853六世- 2021 AB -数字化,音乐信号的分析和处理技术是数字音乐的核心技术。通常有一个预处理过程之前,音乐信号处理。预处理过程通常包括抗锯齿过滤、数字化预加重,窗口和框架。歌曲在流行的MP3格式wav格式和在互联网上都是歌曲已经被数字技术处理,不需要数字化。预处理可以影响的有效性和可靠性的音乐信号的特征参数提取。因为音乐是一种声音信号,声音的处理也适用于音乐信号。在自适应波动方程反演的研究,传统的全波方程反演使用真实的数据和模拟数据之间的最小均方误差作为目标函数。梯度的方向是由残余波场反向传播的互相关和远期模拟波场对时间的二阶导数。当初始模型之间有很大的差距和正式的模型,周期跳跃的现象将不可避免地出现。在本文中,自适应波动方程反演。 This method adopts the idea of penalty function and introduces the Wiener filter to establish a dual objective function for the phase difference that appears in the inversion. This article discusses the calculation formulas of the accompanying source, gradient, and iteration step length and uses the conjugate gradient method to iteratively reduce the phase difference. In the test function group and the recorded music signal library, a large number of simulation experiments and comparative analysis of the music signal recognition experiment were performed on the extracted features, which verified the time-frequency analysis performance of the wave equation inversion and the improvement of the decomposition algorithm. The features extracted by the wave equation inversion have a higher recognition rate than the features extracted based on the standard decomposition algorithm, which verifies that the wave equation inversion has a better decomposition ability. SN - 1687-9120 UR - https://doi.org/10.1155/2021/8678853 DO - 10.1155/2021/8678853 JF - Advances in Mathematical Physics PB - Hindawi KW - ER -