Abstract
This paper presents the equalization of channel distortion by using a Nonlinear Neuro-Fuzzy Network (NNFN). The NFNN is constructed on the basis of fuzzy rules that incorporate nonlinear functions. The learning algorithm of NNFN is presented. The NFNN is applied for equalization of channel distortion of time-invariant and time-varying channels. The developed equalizer recovers the transmitted signal efficiently. The performance of NNFN based equalizer is compared with the performance of other nonlinear equalizers. The effectiveness of the proposed system is evaluated using simulation results of NNFN based equalization system.
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Abiyev, R.H., Mamedov, F., Al-shanableh, T. (2007). Equalization of Channel Distortion Using Nonlinear Neuro-Fuzzy Network. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_30
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DOI: https://doi.org/10.1007/978-3-540-72393-6_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
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