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ODMTCNet: An Interpretable Multi-view Deep Neural Network Architecture for Image Feature Representation
This work proposes an interpretable multi-view deep neural network architecture, namely optimal discriminant multi-view tensor convolutional network (ODMTCNet), by integrating statistical machine learning (SML) principles with the deep neural network (DNN) architecture.
Multi-Layered Recursive Least Squares for Time-Varying System Identification
It is shown that the mean square error (MSE) of the m-RLS estimate can be minimized by selecting the optimum number of layers.
An Adaptive Receiver for Underwater Acoustic Full-Duplex Communication with Joint Tracking of the Remote and Self-Interference Channels
Full-duplex (FD) communication is a promising candidate to address the data rate limitations in underwater acoustic (UWA) channels.
Self-Interference Channel Characterization in Underwater Acoustic In-Band Full-Duplex Communications Using OFDM
However, in UWA-IBFD, because of reflections from the surface and bottom and the inhomogeneity of the water, a significant part of the transmitted signal returns back to the IBFD receiver.
