Optical-mode neural network by use of the nonlinear response of a laser diode to external optical feedback

Applied Optics

Volumn 36, Issue 26, 1997, Pages 6654-6663

  Mos, E C ^a   Schleipen, J J H B ^a   de Waardt, H ^b  

^a PHILIPS RESEARCH LABORATORIES   (Netherlands)

^b EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Laser diodes; Optical computing; Optical feedback; Optical neural networks; Stochastic learning algorithm

Indexed keywords

LASER BEAMS; LEARNING ALGORITHMS; LENSES; LIQUID CRYSTAL DISPLAYS; MIRRORS; OPTICAL DATA PROCESSING; OPTIMIZATION; PERSONAL COMPUTERS; QUANTUM WELL LASERS; SEMICONDUCTOR LASERS;

LASER NEURAL NETWORK; LONGITUDINAL CAVITY MODES; OPTICAL MATRIX VECTOR MULTIPLIER; OPTICAL MODE NEURAL NETWORK; OPTICAL MULTICHANNEL ANALYZER;

NEURAL NETWORKS;

EID: 0031237689     PISSN: 1559128X     EISSN: 21553165     Source Type: Journal    
DOI: 10.1364/AO.36.006654     Document Type: Article

References (22)

1. D. Hammerstrom and S. Rehfuss, “Neurocomputinghardware: present and future,” Art. Intell. Rev. 7, 285-300 (1993).
2. A. Jennings, P. Horan, and J. Hegarty, “Optical neural network with quantum well devices,” Appl. Opt. 33, 1469-1476 (1994).
3. A. Hirose and R. Eckmiller, “Coherent optical neural networks that have optical-frequency-controlled behavior and generalization ability in the frequency domain,” Appl. Opt. 35, 836-843 (1996).
4. B. Javidi, J. Li, and Q. Tang, “Optical implementation of neural networks for face recognition by the use of nonlinear joint transform correlators,” Appl. Opt. 34, 3950-3962 (1995).
5. I. Saxena and E. Fiesler, “Adaptive multilayer optical neural network with optical thresholding,” Opt. Eng. 34, 2435-2440 (1995).
6. S. Juthamulia and F. T. S. Yu, “Overview of hybrid optical neural networks,” Opt. Laser Technol. 28, 59-72 (1996).
7. F. T. S. Yu, “Optical neural networks: architecture, design and models,” in Progress in Optics, E. Wolf, ed. (North Holland, Amsterdam, 1993), Vol. 32, pp. 61-144.
8. S. B. Colak, J. J. H. B. Schleipen, and C. T. H. Liedenbaum, “Neural network using longitudinal modes of an injection laser with external feedback,” IEEE Trans. Neural Networks 7, 1389-1400 (1996).
9. J. J. H. B. Schleipen, S. B. Colak, E. C. Mos, and C. T. H. Liedenbaum, “An injection laser neural network,” in Proceedings of the Fourth International Conference on Microelectronics for Neural Networks and Fuzzy Systems (IEEE Computer Society Press, Los Alamitos, Calif., 1994), pp. 8-12.
10. K. Petermann, “Laser diode modulation and noise,” in Advances in Optoelectronics T. Okoshi, ed. (Kluwer Academic, Dordrecht, The Netherlands, 1991).
11. J. Sacher, W. Elsasser, and E. O. Gobel, “Nonlinear dynamics of semiconductor laser emission under variable feedback conditions,” IEEE J. Quantum Electron. 27, 373-379 (1991).
12. A. E. Siegman, Lasers (University Science, Mill Valley, Calif., 1986).
13. G. P. Agrawal and N. K. Dutta, Long Wavelength Semiconductor Lasers (Van Nostrand Reinhold, New York, 1986), Chap. 6.
14. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, “Learning internal representation by error propagation,” in Parallel Dis-tributed Processing, D. E. Rumelhart and J. L. McClelland, eds. (MIT Press, Cambridge, Mass., 1986), Vol. 1, pp. 318-362.
15. Y. Maeda, H. Hirano, and Y. Kanata, “A learning rule of neural networks via simultaneous perturbation and its hardware implementation,” Neural Networks 8, 251-259 (1995).
16. J. Alspector, R. B. Allen, V. Hu, and S. Satyanarayana, “Stochastic learning networks and their electronic implementation,” in Neural Information Processing Systems, D. Z. Anderson, ed. (American Institute of Physics, Denver, Colo., 1988), pp. 9-21.
17. H. Szu and R. Hartley, “Fast simulated annealing,” Phys. Lett. A 122, 157-162 (1987).
18. S. Geman and D. Geman, “Stochastic relaxation, Gibbs distribution and Baysian restoration of images,” IEEE Trans. Pattern Anal. Machine Intell. 6, 721-741 (1984).
19. J. Sun, W. I. Grosky, and H. Hassoun, “A fast algorithm for finding global minima of error functions in layered neural networks,” in Proceedings of the International Joint Conference on Neural Networks (IEEE Neural Network Council, Ann Arbor, Mich., 1990), Vol. 1, pp. 715-720.
20. N. Baba, “A new approach for finding the global minimum of error function of neural networks,” Neural Networks 2, 367-373 (1989).
21. P. D. Wasserman, Neural Computing, Theory and Practice (Van Nostrand Reinhold, New York, 1989).
22. T. P. Lee, C. A. Burrus, J. A. Copeland, A. G. Dentai, and D. Marcuse, “Short cavity InGaAsP injection lasers: dependence of mode spectra and single-longitudinal-mode power on cavity length,” IEEE J. Quantum Electron. 18, 1101-1113 (1982).