volume | PIER Journals

Abstract

This paper introduces a deep neural network (DNN) training framework to tackle the general power pattern synthesis problem. Compared to the iterative solving method, the DNN-based approach offers a shorter response time, which is significant in adaptive scenarios. In contrast to the widely adopted supervised learning framework, the encoder-decoder network structure utilized in this paper does not necessitate the pre-synthesized results as the training label. The issue of difficult convergence in training caused by the non-uniqueness of the solution is well solved in our method.

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Dr. Lu Zhuang

Dr. Jun Ou Yang