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Music teaching platform based on FPGA and neural network

机译：基于FPGA和神经网络的音乐教学平台

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This model describes a new way for students majoring in music training to teach specific topics in advanced music system. Projects are typically designed to address the lack of enthusiasm and participation, so that the end of course students have extraordinary interest to learn music. The music teaching of the student with help of neural network and FPGA, after that the learning is completed to conduct the examination process about the music course to validate the student. A minimal effort range analyzer works from a modified FPGA (Field Programmable Gate Array) board. The neural network is used to create the platform of music student and to reduce the risk of data management in the class room. The processing of the network depends on the weight of the connections between those nodes that have been trained or adapted to the training dataset, and this process is commonly referred to as network training or learning. Not only are the students improving performance, therefore in this system compared to the significance of the existing model educated in this music course. A few understudies have likewise demonstrated compassion towards traditional music that they had never heard.
机译：该模型描述了专注于音乐培训的学生的新方法，以教导先进音乐系统中的特定主题。项目通常旨在解决缺乏热情和参与，因此学生的结束是学习音乐的非凡兴趣。在神经网络和FPGA的帮助下，学生的音乐教学，之后学习完成了关于验证学生的音乐课程的考试过程。最小的努力范围分析仪从修改的FPGA（现场可编程门阵列）板工作。神经网络用于创建音乐学生的平台，并降低类别室内数据管理的风险。网络的处理取决于已经训练或适于训练数据集的那些节点之间的连接的权重，并且该过程通常被称为网络训练或学习。因此，不仅是学生提高性能，因此在该系统中与本音乐课程中现有模型的重要性相比。一些人认为同样对他们从未听过的传统音乐表现出同情。

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