Cite
HARVARD Citation
Ferracuti, F. et al. (n.d.). Electric motor defects diagnosis based on kernel density estimation and Kullback–Leibler divergence in quality control scenario. Engineering applications of artificial intelligence. pp. 25-32. [Online].