Binary neuro-fuzzy classifiers trained by nonlinear quantum circuits

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4578 LNAI, Issue , 2007, Pages 237-244

  Panella, Massimo ^a   Martinelli, Giuseppe ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; LEARNING SYSTEMS; NONLINEAR SYSTEMS; OPTIMIZATION; PROBLEM SOLVING; QUANTUM COMPUTERS;

BINARY CLASSIFICATION; FUZZY CLASSIFIERS; NONLINEAR QUANTUM CIRCUITS; QUANTUM PROCESSING;

FUZZY LOGIC;

EID: 37249059883     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73400-0_29     Document Type: Conference Paper

References (13)

1. Los Alamos preprint server: available at http://xxx.lanl.gov/archive/ quant-ph
2. Perkowski, M.: Multiple-valued quantum circuits and research challenges for logic design and computational intelligence communities. IEEE Connections 3, 6-12 (2005)
3. Frayman, Y., Wang, L.: Data mining using dynamically constructed recurrent fuzzy neural networks. In: Wu, X., Kotagiri, R., Korb, K.B. (eds.) PAKDD 1998. LNCS, vol. 1394, pp. 122-131. Springer, Heidelberg (1998)
4. Held, C., Heiss, J., Estevez, P., Perez, C., Garrido, M., Algarin, C., Peirano, P.: Extracting fuzzy rules from Polysomnographic recordings for infant sleep classification. IEEE Trans. on Biomedical Engineering 53, 1954-1962 (2006)
5. Jang, J.S.: ANFIS: Adaptive-network-based fuzzy inference system. IEEE Trans. on Systems, Man and Cybernetics 23, 665-685 (1993)
6. Wang, L., Fu, X.: Data Mining with Computational Intelligence. Springer, Berlin (2005)
7. Wang, W., Ismail, F., Golnaraghi, F.: A neuro-fuzzy approach to gear system monitoring. IEEE Trans. on Fuzzy Systems 12, 710-723 (2004)
8. Haykin, S.: Neural Networks, a Comprehensive Foundation, 2nd edn. Prentice-Hall, Englewood Cliffs, NJ, USA (1999)
9. Rieffel, E., Polak, W.: An introduction to quantum computing for non-physicists. ACM Computing Surveys 32, 300-335 (2000)
10. Deutsch, D.: Quantum theory, the Church-Turing principle and the universal quantum compute. In: Proc. of the Royal Society of London, vol. A 400, pp. 97-117 (1985)
11. Grover, L.: A fast quantum mechanical algorithm for database search. In: Proc. of the 28th Annual ACM Symposium on the Theory of Computing, Philadelphia, Pennsylvania, USA, pp. 212-219 (1996)
12. Abrams, D., Lloyd, S.: Nonlinear quantum mechanics implies polynomial-time solution for NP-complete and #P problems. Phys. Rev. Lett. 81, 3992-3995 (1998)
13. Gupta, S., Zia, R.: Quantum neural networks. Journal of Computer and System Sciences 63, 355-383 (2001)