[HTML][HTML] Implementation of Bartlett matched-field processing using interpretable complex convolutional neural network
Neural networks have been applied to underwater source localization and achieved better
performance than the conventional matched-field processing (MFP). However, compared
with MFP, the neural networks lack physical interpretability. In this work, an interpretable
complex convolutional neural network based on Bartlett processor (BC-CNN) for underwater
source localization is designed, the output and structure of which have clear physical
meanings. The relationship between the convolution weights of BC-CNN and replica …
performance than the conventional matched-field processing (MFP). However, compared
with MFP, the neural networks lack physical interpretability. In this work, an interpretable
complex convolutional neural network based on Bartlett processor (BC-CNN) for underwater
source localization is designed, the output and structure of which have clear physical
meanings. The relationship between the convolution weights of BC-CNN and replica …
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