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24 November 2009Degraded parameter estimation using quantum neural network
In this paper, an approach based on the quantum neural network is investigated to guide the process of selecting an
optimal estimation of Gaussian degraded parameter. In fact, we first formulate the nonlinear problem by maximum
likelihood estimation. Then we modify and apply the quantum neural network algorithm, which combines the advantages
of both quantum computing and neural computing, to solve the optimal estimation problem. The new algorithm does not
suffer from the morass of selecting good initial values and being stuck into local optimum as usually accompanied with
the conventional techniques. The simulation results indicate the soundness of the new method.
Yan Zhang,Kun Gao,Guoqiang Ni, andTingzhu Bai
"Degraded parameter estimation using quantum neural network", Proc. SPIE 7513, 2009 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Process Technology, 75132I (24 November 2009); https://doi.org/10.1117/12.838199
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Yan Zhang, Kun Gao, Guoqiang Ni, Tingzhu Bai, "Degraded parameter estimation using quantum neural network," Proc. SPIE 7513, 2009 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Process Technology, 75132I (24 November 2009); https://doi.org/10.1117/12.838199