Abstract
A novel neural network,quantum perceptron network(QPN), is presented built upon the combination of classical perceptron network and quantum computing.This quantum perceptron network utilizing quantum phase adequately has the computing power that the conventional perceptron is unable to realize. Through case’ performance analysis and simulation,a quantum perceptron with only one neuron can realize XOR function unrealizable with a classical perceptron having a neuron. Simple network structure can achieve comparatively complicated network function,which will throw heavy influence on the field of artificial intelligence and control engineering.
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References
Kak, S.C.: On Quantum Neural Computing. Information Sciences 83, 143–160 (1995)
Nitta, T.: An Extension of the Back-Propagation Algorithm to Complex Numbers. Neural Networks 10(8), 1391–1415 (1997)
Menneer, T.: Quantum Artificial Neural Networks. Ph. D. thesis of The Univ. of Exeter, UK (1998)
Menneer, T., Narayanan, A.: Quantum-inspired Neural Networks.Tech. Rep. R329, Univ. of Exeter (1995)
Wei-gang, L.: Entangled Neural Networks, http://www.cic.unb.br/weifang/qc/enn2000.pdf
Ventura, D., Martinez, T.R.: Quantum Associative Memory. Information Sciences 124, 273–296 (2000)
Ezhov, A.A., Nifanova, A.V., Ventura, D.: Quantum associative memory with distributed queries. Information Sciences 128, 271–293 (2000)
Ventura, D., Martinez, T.R.: Quantum Associative Memory. Information Sciences 124, 273–296 (2000)
Altaisky, M.V.: Quantum neural network.Technical report (2001), http://xxx.lanl.gov/quantph/0107012
Nielsen, M., Chuang, I.: Quantum Computation and Quantum Information. Cambridge University Press, Cambridge (2000)
Kouda, N., Matsui, N., Nishimura, H., Peper, F.: Qubit Neural Network and Its Efficiency. In: Palade, V., Howlett, R.J., Jain, L. (eds.) KES 2003. LNCS, vol. 2774, pp. 304–310. Springer, Heidelberg (2003)
Kouda, N., Matsui, N., Nishimura, H., Peper, F.: Qubit Neural Network and Its Learning Efficiency. Neural Computing and Applications. Springer, Heidelberg (2005), DOI:10.1007/ s00521-004 -0446-8
Kouda, N., Matsui, N., Nishimura, H., Peper, F.: An Examination of Qubit Neural Network in Controlling an Inverted Pendulum. Neural Processing Letters 22, 277–290 (2005)
Kouda, N., Matsui, N., Nishimura, H.: Image compression by layered quantum neural networks. Neural Processing Letters 16(1), 67–80 (2002)
Ricks, B., Ventura, D.: Training a Quantum Neural network, http://books.nips.cc/papers/files/nips16/NIPS2003_ET05.pdf
Fei, L., Shengmei, Z., Baoyu, Z.: Performance of a single quantum neuron. Chinese Journal of Electronics 14(1), 111–114 (2005)
Guangjun, X., Zhenquan, Z.: A Quantum Computitive Learning Algorithm. Chinese Journal Of Quantum Electronics 20(1) (February 2003) (in Chinese)
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhou, R., Qin, L., Jiang, N. (2006). Quantum Perceptron Network. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_68
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DOI: https://doi.org/10.1007/11840817_68
Publisher Name: Springer, Berlin, Heidelberg
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