Research on Classification of Carbon Content in Pr-Nd Alloys Based on MFCC and BP Neural Network-Reference-Cited by-同舟云学术

Research on Classification of Carbon Content in Pr-Nd Alloys Based on MFCC and BP Neural Network

Published:2021-10-22 Issue: Volume: Page:
ISSN:
Container-title:2021 China Automation Congress (CAC)
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Author:

Wu Xinyu¹,Chen Xinyu²,Liu Feifei³,Wang Linsheng¹,Li Jiahao²,Chen Shumei⁴

Affiliation:

1. Jiangxi Ionic Rare Earth Engineering Research Co. Led.,Ganzhou,China

2. Jiangxi University of Science and Technology,School of Mechanical and Electrical Engineering,Ganzhou,China

3. Jiangxi University of Science and Technology,School of Electrical Engineering and Automation,Ganzhou,China

4. Jiangxi University of Science and Technology,Faculty of Materials Metallurgy and Chemistry,Ganzhou,China

Funder

Natural Science Foundation of Jiangxi Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9727224/9727236/09727226.pdf?arnumber=9727226

Reference27 articles.

1. Evaluation and modeling of automotive transmission whine noise quality based on MFCC and CNN

2. A low latency modular-level deeply integrated MFCC feature extraction architecture for speech recognition[J];robinson;Integration the VLSI Journal,2020

3. Understanding nonverbal communication cues of human personality traits in human-robot interaction

4. Contact Feature Recognition Based on MFCC of Force Signals

5. Speech Magnitude Spectrum Reconstruction from MFCCs Using Deep Neural Network

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1. Recognition of Carbon Content of Pr-Nd Alloys Based on Mel-Frequency Cepstrum Coefficient of Force Signals;JOM;2022-07-25