Publication: The realization of quantum complex-valued backpropagation neural network in pattern recognition problem
Issued Date
2002-01-01
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2-s2.0-84965077460
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Mahidol University
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SCOPUS
Bibliographic Citation
ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. Vol.1, (2002), 462-466
Suggested Citation
J. L. Mitrpanont, A. Srisuphab The realization of quantum complex-valued backpropagation neural network in pattern recognition problem. ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age. Vol.1, (2002), 462-466. doi:10.1109/ICONIP.2002.1202213 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/20142
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Title
The realization of quantum complex-valued backpropagation neural network in pattern recognition problem
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Abstract
© 2002 Nanyang Technological University. The paper presents the approach of the quantum complex-valued backpropagation neural network or QCBPN. The challenge of our research is the expected results from the development of the quantum neural network using complex-valued backpropagation learning algorithm to solve classification problems. The concept of QCBPN emerged from the quantum circuit neural network research and the complex-valued backpropagation algorithm. We found that complex value and the quantum states share some natural representation suitable for the parallel computation. The quantum circuit neural network provides a qubit-like neuron model based on quantum mechanics with quantum backpropagation-learning rule, while the complex-valued backpropagation algorithm modifies standard backpropagation algorithm to learn complex number pattern in a natural way. The quantum complex-valued neuron model and the QCBPN learning algorithm are described. Finally, the realization of the QCBPN is exploited with a simple pattern recognition problem.