Abstract
Quantum computation uses quantum mechanical concepts to perform computational tasks and in some cases its results are exponentially faster than their classical counterparts. The main practical reason to investigate the quantum concepts on artificial neural computation is motivated by the success of some quantum algorithms like Grover’s search algorithm and Shore’s factoring algorithm. The neural networks can be advanced more by the application of quantum computing on artificial neural network (ANN). Since quantum physics is the natural generalization of classical physics, the classical ANN can be generalized to its quantum domain by the combination of classical neural computation with quantum computation. In this paper we have tried to introduce basic quantum mechanical concepts in artificial neural computation.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kak, S.C.: On Quantum Neural Computing. Information Science 83, 143–160 (1995)
Menneer, T., Narayanan, A.: Quantum-inspired Neural Networks. Tech. Rep. R329, Univ. of Exeter (1995)
Benioff, P.A.: Quantum Mechanical Hamiltonian Model of Turing Machine. J. Stat. Phy., R. 29(3), 515–546 (1982)
Feynman, R.P.: Simulating physics with computers. Inr. J. of Theo. Physics 21(6/7), 467–488 (1982)
Deutsch, D.: Quantum theory, the Church-Turing principle and the universal quantum computer. Pmc. of Roy. Soc. of London Ser. A 400, 97–117 (1985)
Minsky, M., Papert, P.: Perceptrons: An Introduction to Computational Geometry. MIT Press, Cambridge (1969)
Ezhov, A., Ventura, D.: Quantum Neural Networks. In: Future Directions for lnielligent Systems and Information Sciences, pp. 213–234. Springer, Heidelberg (2000)
Altaisky, M.V.: Quantum neural network, ArXiv: quant-ph/O l07012 (2001)
Landman, B.S., Russo, R.L.: IEEE Transactions on Computers 20, 1469–1479 (1971)
Ezhov, A.A., Shumsky, S.A.: Neurocomputing and its application in economics and business. Moscow Engineering Physics Institutes, Moscow (1999)
Nakahara, M., Tetsuo, O.: Quantum Computing, From Linear Algebra to Physical Realizations. CRC Pres, Boca Raton (2008)
Nielsen, M.A., Chuang, I.L.: Quantum computation and Quantum Information Chuang. Cambridge University press (2002)
Rieffel, E., Polak, W.: An Introduction to Quantum Computing for Non- Physicists. ACM Computing Surveys (CSUR) 32(3), 300–335 (2000)
Ezhov, A.A., Berman, G.P.: Introduction to Quantum Neural Technologies. Rinton Press, New Jersey (2003)
Menneer, T., Narayanan, A.: Quantum artificial neural network architectures and components. Information Sciences (128), 231–255 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer India Pvt. Ltd.
About this paper
Cite this paper
Nayak, S., Nayak, S., Singh, J.P. (2012). Quantum Concepts in Neural Computation. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 130. Springer, India. https://doi.org/10.1007/978-81-322-0487-9_40
Download citation
DOI: https://doi.org/10.1007/978-81-322-0487-9_40
Published:
Publisher Name: Springer, India
Print ISBN: 978-81-322-0486-2
Online ISBN: 978-81-322-0487-9
eBook Packages: EngineeringEngineering (R0)