Classification of the Type of Harmonic Source Based on Image-Matrix Transformation and Deep Convolutional Neural Network
The classification of harmonic source types is a necessary step to alleviate harmonic pollution. This study proposes a method for the harmonic source classification based on 2-D image-matrix transformation (IMT) and deep convolutional neural network (CNN). The method firstly converts the V-I wavefor...
Main Authors: | Fei Mei, Haoyuan Sha |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8906105/ |
Similar Items
-
Sparse Matrix Classification on Imbalanced Datasets Using Convolutional Neural Networks
by: Juan C. Pichel, et al.
Published: (2019-01-01) -
Variable Convolution and Pooling Convolutional Neural Network for Text Sentiment Classification
by: Min Dong, et al.
Published: (2020-01-01) -
Deep convolutional neural network based medical image classification for disease diagnosis
by: Samir S. Yadav, et al.
Published: (2019-12-01) -
Multi-Harmonic Sources Harmonic Contribution Determination Based on Data Filtering and Cluster Analysis
by: Haoyuan Sha, et al.
Published: (2019-01-01) -
Pneumonia Classification of Thorax Images using Convolutional Neural Networks
by: Mahmud Suyuti, et al.
Published: (2020-07-01)