Quadratic Residual Multiplicative Filter Neural Networks for Efficient Approximation of Complex Sensor Signals
In this research, we present an innovative Quadratic Residual Multiplicative Filter Neural Network (QRMFNN) to effectively learn extremely complex sensor signals as a low-dimensional regression problem. Based on this novel neural network model, we introduce two enhanced architectures, namely Fourier...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10189900/ |