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Neural Networks-Based Nonlinear Equalizer for Super-RENS Discs  

Seo, Man-Jung (School of Electronic Engineering, Soongsil University)
Im, Sung-Bin (School of Electronic Engineering, Soongsil University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea TC / v.45, no.12, 2008 , pp. 90-96 More about this Journal
Abstract
Recently, various recording technologies are studied for optical data storage. After standardization of BD (Blu-ray Disc) and HD-DVD (High-Definition Digital Versatile Disc), the industry is looking for a suitable technology for next generation optical data storage. Super-RENS (Super-Resolution Near Field Structure) technique, which is capable of compatibility with other systems, is one of next optical data storage. In this paper, we proposed a neural network-based nonlinear equalizer (NNEQ) for Super-RENS discs. To mitigate the nonlinear ISI (Inter-Symbol Interference), we applied NARX (Nonlinear AutoRegressive eXogenous) which is a kind of neural networks. Its validity is tested with the RF signal samples obtained from a Super-RENS disc. The performance of the proposed equalizer is superior to the one without equalization and that of the Limit-EQ in terms of BER (Bit Error Rate).
Keywords
Super-RENS; neural network; equalizer; nonlinearity; NARX;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 T. Kikukawa, T. Nakano, T. Shima, and J. Tominaga, "Rigid bubble pit formation and huge signal enhancement in super-resolution near-field structure disk with platinum-oxide layer," Appl. Phys. Lett., vol. 81, no. 25, pp. 4697-4699, Dec. 2002   DOI   ScienceOn
2 H. Fuji, J. Tominaga, T. Nakano, N. Atoda, and H. Katayama, Technical Digest of the Joint International Symposium on Optical Memory and Optical Data Storage, pp. TuD29, Jul. 1999
3 T. Kikukawa, N. Fukuzawa, and T. Kobayashi, "Properties of Super-Resolution Near-Field Structure with Platinum-Oxide Layer in Blu-ray Disc System," Japanese Journal of Applied Physics, Vol. 44, Part 1, no. 5B, pp. 3596-3597, May 2005   DOI
4 B. Yuhas, and N. Ausari, Neural networks in telecommunication, Kluwer Academic Publisher, 1994
5 Hagan, M,T., and M.Menhaj, "Training feed-forward networks with the Marquardt algorithm," IEEE Trans. on Neural Networks, vol. 5, no. 6, pp. 989-993, 1999   DOI   ScienceOn
6 Powell, M.J.D., "Restart procedures for the conjugate gradient method," Mathematical Programming, vol. 12, pp. 241-254, 1977   DOI
7 H. Kobayashi, H. Kuribayashi, Y. Tomita, and S. Ohsawa, "Effects of Limit Equalizer in Blu-ray Disc Format," IEEE Transaction on Consumer Electronics, vol. 49, no. 4, pp. 1141-1147, Nov. 2003   DOI   ScienceOn
8 D. P. Tsai, and W. C. Lin, "Probing the near fields of the super-resolution near-field optical structure," Appl. Phys. Lett., vol. 77, no. 10, pp. 1413-1415, Sep. 2000   DOI   ScienceOn
9 Riedmiller, M., and H. Braun, "A direct adaptive method for faster backpropagation learning: The RPROP algorithm," Proceedings of the IEEE International Conference on Neural Networks, 1993
10 김주호, 황인오, 김현기, 윤두섭, 박인식, "Optical Memory Disc Using Super-resolution Phenomenon of Super-RENS Technology," Optical Society of Korea Annual Meeting 2004, pp. 248-251, Feb. 2004
11 박강호, 김영주, 박노철, 김수경, 곽금철, "근접장 광 정보저장 기술 동향," Optical Science and Technology, Vol. 9, no. 2, pp. 12-21, Apr. 2005
12 J. Tominaga, T. Nakano, and N. Atoda, "An approach for recording and readout beyond the diffraction limit with an Sb thin film," Appl. Phys. Lett., vol. 73, no. 15, pp. 2078-2080, Oct. 1998   DOI   ScienceOn
13 T. Nakano, A. Sato, H. Fuji, J. Tominaga, and N. Atoda, "Transmitted signal detection of optical disks with a superresolution near-field structure," Appl. Phys. Lett., vol. 75, no. 2, pp. 151-153, Jul. 1999   DOI
14 http://www.blu-raydisc.com/en.html
15 Battiti, R., "First and second order methods for learning: Between steepest descent and Newton's method," Neural Computation, vol. 4, no. 2, pp. 141-166, 1992   DOI
16 서만중, 임성빈, 이재진, "신경망을 이용한 Super-RENS 시스템의 비선형 모델링," 대한전자공학회 논문지, vol. 45, no. 3, pp. 53-60, 2008년 3월   과학기술학회마을
17 J. B. Gomm, D. L. Yu, and D. Williams, "A new model structure selection method for non-linear systems in neural modelling," UKACC International Conference on Control '96, Vol. 2, no. 427, pp. 752-757, 1996
18 K. Kwak, S. Kim, C. Lee, and K. Song, "New materials for super-resolution disc," SPIE Proceedings, vol. 6620, ODS2007 TuC5, 2007
19 J. Tominaga, H. Fuji, A. Sato, T. Nakano, and N. Atoda, "The characteristics and potential of super resolution near-field structure," Japanese Journal of Applied Physics, Vol. 39, Part 1, no. 2B, pp. 957-961, Feb. 2000   DOI
20 Moller, M.F., "A scaled conjugate gradient algorithm for fast supervised learning," Neural Networks, vol. 6, pp. 525-533, 1993   DOI   ScienceOn
21 Dennis, J.E., and R.B. Schnabel, Numerical Methods for Unconstrained Optimization and Nonlinear Equations, Englewood Cliffs, NJ: Prentice-Hall, 1983