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This paper presents a quantum-based algorithm for evolving artificial neural networks (ANNs). The aim is to design an ANN with few connections and high classification performance by simultaneously optimizing the network structure and the connection weights. Unlike most previous studies, the proposed algorithm uses quantum bit representation to codify the(More)
In this paper the non-stationary power signal prediction by using quantum neural network (QNY) is proposed. The signals with fuzziness are expected to be classged clearly for enhancing the learning eflciency of neural network due to the hidden units with various g,-aded levels in QNN structure. For a comparison, all experLwents are also performed by using(More)