Experimental demonstration of reservoir computing on a silicon photonics chip

Nature Communications

Volumn 5, Issue , 2014, Pages

  Vandoorne, Kristof ^a,b   Mechet, Pauline ^a,b   Van Vaerenbergh, Thomas ^a,b   Fiers, Martin ^a,b   Morthier, Geert ^a,b   Verstraeten, David ^b   Schrauwen, Benjamin ^b   Dambre, Joni ^b   Bienstman, Peter ^a,b  

^a IMEC   (Belgium)

^b GHENT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

SILICON;

ADVANCED TECHNOLOGY; DATA INTERPRETATION; EXPERIMENTAL STUDY; MACHINE LEARNING; PARADIGM SHIFT; SILICON;

ARTICLE; BIOCHIP; COMPUTER; INFORMATION SCIENCE; MACHINE LEARNING; MATHEMATICAL COMPUTING; OPTICS; RECOGNITION; RESERVOIR; RESERVOIR COMPUTING; SIMULATION;

EID: 84899836505     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms4541     Document Type: Article

References (29)

1. Jaeger, H. & Haas, H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science 304, 78-80 (2004).
2. Maass, W., Natschlager, T. & Markram, H. Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural. Comput. 14, 2531-2560 (2002).
3. Hammer, B. & Steil, J. J. in European Symposium Artificial Neural Networks (ESANN) 357-368 (2002).
4. Pearlmutter, B. Gradient calculations for dynamic recurrent neural networks: a survey. IEEE Trans. Neural Netw. 6, 1212-1228 (1995).
5. Legenstein, R. & Maass, W. What makes a dynamical system computationally powerful? New Directions in Statistical Signal Processing: From Systems to Brains 127-154 (MIT Press, 2007).
6. Maass, W., Joshi, P. & Sontag, E. D. Computational aspects of feedback in neural circuits. PLoS Comput. Biol. 3, e165 (2007).
7. Skowronski, M. D. & Harris, J. G. Automatic speech recognition using a predictive echo state network classifier. Neural Netw. 20, 414-423 (2007).
8. Antonelo, E. A., Schrauwen, B. & Stroobandt, D. Event detection and localization for small mobile robots using reservoir computing. Neural Netw. 21, 862-871 (2008).
9. Wyffels, F. & Schrauwen, B. A comparative study of reservoir computing strategies for monthly time series prediction. Neurocomputing 73, 1958-1964 (2010).
10. Jaeger, H. Short Term Memory in Echo State Networks. Technical Report 152 (GMD, Berlin, 2001).
11. Verstraeten, D., Schrauwen, B., Suykens, J. A. K., Stroobandt, D. & Vandewalle, J. in International Symposium on Nonlinear Theory and its Applications (NOLTA) 101-104 (2008).
12. Fernando, C. & Sojakka, S. Pattern recognition in a bucket. Adv Artif Life 588-597 (2003).
13. Jones, B., Stekel, D., Rowe, J. & Fernando, C. in IEEE Symposium on Artificial Life (ALIFE) '07 187-191 (2007).
14. Appeltant, L. et al. Information processing using a single dynamical node as complex system. Nat. Commun. 2, 468 (2011).
15. Brunner, D. et al. Parallel photonic information processing at gigabyte per second data rates using transient states. Nat. Commun. 4, 1364 (2013).
16. Larger, L. et al. Photonic information processing beyond turing: an optoelectronic implementation of reservoir computing. Opt. Express 20, 3241-3249 (2012).
17. Duport, F., Schneider, B., Smerieri, A., Haelterman, M. & Massar, S. All-optical reservoir computing. Opt. Express 20, 22783 (2012).
18. Martinenghi, R., Rybalko, S., Jacquot, M., Chembo, Y. & Larger, L. Photonic nonlinear transient computing with multiple-delay wavelength dynamics. Phys. Rev. Lett. 108, 244101 (2012).
19. Mesaritakis, C., Papataxiarhis, V. & Syvridis, D. Micro ring resonators as building blocks for an all-optical high-speed reservoir-computing bit-pattern-recognition system. J. Opt. Soc. Am. B 30, 3048-3055 (2013).
20. Vandoorne, K., Dambre, J., Verstraeten, D., Schrauwen, B. & Bienstman, P. Parallel reservoir computing using optical amplifiers. IEEE Trans. Neural Netw. 22, 1469-1481 (2011).
21. Bogaerts, W. & Selvaraja, S. K. Compact Single-Mode Silicon Hybrid Rib/Strip Waveguide With Adiabatic Bends. IEEE Photonics J. 3, 422-432 (2011).
22. Roelkens, G. et al. Grating-based optical fiber interfaces for Silicon-on-Insulator photonic integrated circuits. IEEE J. Sel. Top. Quant. Elect. 17, 571-580 (2011).
23. Liu, J., Sun, X., Camacho-Aguilera, R., Kimerling, L. C. & Michel, J. Ge-on-Si laser operating at room temperature. Opt. Lett. 35, 679-681 (2010).
24. Roelkens, G. et al. III-V/silicon photonics for on-chip and intra-chip optical interconnects. Laser Photonics Rev. 4, 751-779 (2010).
25. Fiers, M. et al. Time-domain and frequency-domain modeling of nonlinear optical components at the circuit-level using a node-based approach. JOSA B 29, 896-900 (2012).
26. Doddington, G. R. & Schalk, T. B. Computers - Speech Recognition - Turning Theory to Practice. {IEEE} Spectrum 18, 26-32 (1981).
27. Lyon, R. in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 7, 1282-1285 (1982).
28. Tikhonov, A. N. & Arsenin, V. I. Solutions of ill-posed problems (Winston, 1977).
29. Selvaraja, S. K. et al. Fabrication of photonic wire and crystal circuits in Silicon-on-Insulator Using 193nm optical lithography. J Lightwave Technol 27, 4076-4083 (2009).