PhaseDNN - A Parallel Phase Shift Deep Neural Network for Adaptive Wideband Learning

3 May 2019Wei CaiXiaoguang LiLizuo Liu

In this paper, we propose a phase shift deep neural network (PhaseDNN) which provides a wideband convergence in approximating a high dimensional function during its training of the network. The PhaseDNN utilizes the fact that many DNN achieves convergence in the low frequency range first, thus, a series of moderately-sized of DNNs are constructed and trained in parallel for ranges of higher frequencies... (read more)

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