面向智能平台的信号识别算法的Java实现

Ying Xu
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引用次数: 0

摘要

现代信息技术的发展给传统的音乐教学带来了巨大的冲击,并不断推动着我国高校音乐教学方式的变革。然后,提出了一种基于卷积神经网络的钢琴音乐分类方法。将每个分类钢琴曲的谱作为卷积神经网络的输入图像进行训练,通过图像识别间接实现钢琴曲的分类。该方法基于三维飞溅算法。在其他维度的基础上,可以逐维展开,可以更直观地显示多维特征的分布规律。本文采用基于mvc的体系结构,结合Java开发的特点,构建了系统的功能、总体架构和系统数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Java Implementation of Signal Recognition Algorithm Oriented Intelligent Platform
The development of modern information technology has brought a great impact on traditional music teaching, and it is constantly promoting the change of music teaching methods in colleges and universities in our country. Then, a piano music classification method based on convolutional neural network is proposed. The spectrum of each classified piano music is used as the input image of the convolutional neural network for training, and the classification of piano music is indirectly realized through image recognition. The method is based on the three-dimensional Splatting algorithm. On the basis of other dimensions, it can be expanded dimension by dimension, which can more intuitively display the distribution law of multi-dimensional features. This paper adopts the MVC-based architecture and combines the characteristics of Java development to construct the function, overall architecture and system database of the system.
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