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Pacific-Asia Workshop on Computational Intelligence and Industrial Application

Quantum BP Neural Network for speech enhancement

Fei Li, Guobiao Xu

Published Nov 1, 2009• 13 citations
Publisher

Abstract

Quantum Neural Network (QNN), a burgeoning new field which integrates quantum computation with classical neural network, can improve the inadequacies of artificial neural network. A model of quantum neuron and Quantum Back Propagation (BP) Neural Network based on quantum neuron are investigated. A novel approach toward speech enhancement which adopts Quantum BP Neural Network is proposed. The numerical simulation results show that the proposed speech enhancement scheme resulted in better performance than traditional spectral subtraction, Wiener filtering method and RBF neural network.

DOI
10.1109/paciia.2009.5406577

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Quantum Neural Networks(QNN),which integrates the characteristics of artificial neural networks with quantum computing,will become a promising field of information processing.In this paper,a quantum neuron model based on the phase-shift gate and controlled-not gate is constructed with the conventional back propagation learning rule.Its convergence performance is discussed by numerical simulations.Based on this model,a three-layers quantum networks is proposed.The numerical experiments of the identification of noisy English letters show that the proposed quantum networks can identify the noisy English letters efficaciously when the noise variance is less than 0.35,and has more improvement performance in anti-noise than that of conventional Back-Propagation Neural Network.
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It is suggested that a type of artificial neural network can be built using the principles of quantum information processing. A new technique for the recognition of noisy English letter using quantum neural network is proposed in this paper. A qubit neuron model based on quantum mechanics, constructed the quantum back propagation learning rule network (QBP) is given, and a high reliability has been achieved. The numerical experiments of the identification of noisy English letters based on the quantum network has been performed, it is shown that QBP can identify the noised English letters efficaciously; the recognition rate may reach the 100% when the variance of the noise is less than 0.35, and has more improvement performance in anti-noise than that of conventional back propagation neural network, the error recognition rate decreases from 20.46% to 3 % when the noise variance is set to 0.40