¹Depart. Of Electronics and Information Technology,Jiangmen Polytechnic,Jiangmen 529000, China
²Aviation University of Air Force, Changchun 130022, China

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Abstract—This paper proposes a quantum competition neural network model compared to its classical counterpart from the relative parts of the complex system localizing operation without changing the perspective of entanglement measure. It shows that the pseudo-state is an inevitable part of the quantum competitive model. After the initialization of the quantum neural network; quantum competitive network is capable of associative memory through local area of operations because of the existence of these pseudo-states. Furthermore, Competitive algorithms of quantum theory are given, and finally an example of pattern recognition for simulation. Simulation results show that a quantum competitive learning algorithm in the learning rate and convergence rate is far better than the basic competitive artificial neural network.

Index Terms&mdash,Quantum competition network model, quantum associative memory, Pattern recognition, Quantum entanglement.

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Cite: Yanhua Zhong, Changqing Yuan, "Quantum Competition Network Model Based On Quantum Entanglement," Journal of Computers vol. 7, no. 9, pp. 2312-2317, 2012.