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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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초록· 키워드
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In this paper, the minimum mean square error(MSE) convergence of the RBF equalizer is evaluated and compared with the linear equalizer based on the theoretical minimum MSE. The basic idea of comparing these two equalizers comes from the fact that the relationship between the hidden and output layers in the RBF equalizer is also linear. As extensive studies of this research, various channel models are selected, which include linearly separable channel, slightly distorted channel, and severely distorted channel models. In this work, the theoretical minimum MSE for both RBF and linear equalizers were computed, compared and the sensitivity of minimum MSE due to RBF center spreads was analyzed. It was found that RBF based equalizer always produced lower minimum MSE than linear equalizer, and that the minimum MSE value of RBF equalizer was obtained with the center spread which is relatively higher(approximately 2 to 10 times more) than variance of AWGN. This work provides an analytical framework for the practical training of RBF equalizer system.
목차
ABSTRACT
Ⅰ. Introduction
Ⅱ. Background of RBF Equalizer
Ⅲ. Derivation of Minimum Mean Square Errors of RBF Equalizer
Ⅳ. Simulation Studies by Theoretical Approach
Ⅴ. Conclusion
References
저자소개
참고문헌 (12)
참고문헌 신청
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P. R. Chang and B. C. Wang “Adaptive Decision Feedback Equalization for Digital Channels using Multilayer Neural Networks,” IEEE J. Selected Areas Commun., Vol.13, pp.316-324, Feb. 1995.
K. A. Al-Mashouq, I. S. Reed, “The Use of Neural Nets to Combine Equalization with Decoding for Severe Intesymbol Interference Channels,” IEEE Trans. Neural Networks, Vol.5, pp.982-988, Nov. 1994.
S. Chen, B. Mulgrew, and P. M. Grant, “A Clustering Technique for Digital Communication Channel Equalization using Radial Basis Function Networks,” IEEE Trans. Neural Networks, Vol.4, pp.570-579, Jul. 1993.
B. Mulgrew, “Applying Radial Basis Functions,” IEEE Sig. Proc. Mag., pp.50-65, Mar. 1996.
P. R. Chang and B. C. Wang “Adaptive Decision Feedback Equalization for Digital Channels using Multilayer Neural Networks,” IEEE J. Selected Areas Commun., Vol.13, pp.316-324, Feb. 1995.
K. A. Al-Mashouq, I. S. Reed, “The Use of Neural Nets to Combine Equalization with Decoding for Severe Intesymbol Interference Channels,” IEEE Trans. Neural Networks, Vol.5, pp.982-988, Nov. 1994.
S. Chen, B. Mulgrew, and P. M. Grant, “A Clustering Technique for Digital Communication Channel Equalization using Radial Basis Function Networks,” IEEE Trans. Neural Networks, Vol.4, pp.570-579, Jul. 1993.
B. Mulgrew, “Applying Radial Basis Functions,” IEEE Sig. Proc. Mag., pp.50-65, Mar. 1996.
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