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Quantum Information Processing

Can quantum genetic algorithm really improve quantum backpropagation neural network?

Il-Hyang Choe, Gwang-Jin Kim, Nam-Chol Kim, Myong-Chol Ko, Ju-Song Ryom, Ryong-Min Han, Tae-Gyong Han, Il Han

Published Mar 22, 2023• 6 citations
Publisher
DOI
10.1007/s11128-023-03858-w

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A neural network quantum algorithm(NNQA) that employs a genetic quantum algorithm(GQA) and a Hopfield neural network(HNN) for the multiuser detection problem in code-division multiple-access(CDMA) communications system is proposed.Using this algorithm,the Hopfield neural network is embedded into the GQA to improve further the fitness of the population at each generation.Such a hybridization of the GQA with the Hopfield neural network reduces its computational complexity by providing faster convergence.A better initial data estimation supplied by the GQA improves the performance of the HNN,and the embedded Hopfield neural network improves the performance of the GQA.Simulation results show that the proposed approach of multiuser detection has significant performance improvements over conventional detector and the previous detectors based on intelligent algorithms in terms of bit-error-rate,multiple access interference and near-far resistance.