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Orthogonal Wavelet Transform Super-Exponential Iterative Blind Equalization Algorithm Based on Optimization of Genetic Algorithm

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 133))

Abstract

Super-exponential iterative blind equalization algorithm (SEI) has disadvantages of slow convergence rate, big steady-state error and local convergence. In order to overcome these disadvantages, on the basis of analysis of genetic algorithm and orthogonal wavelet transform, this paper proposes an orthogonal wavelet transform super-exponential iterative blind equalization algorithm based on optimization of genetic algorithm. The performance of the proposed algorithm can be improved via fully using the global search of genetic algorithm, the decorrelation ability of orthogonal wavelet transform and the whitening ability of SEI. Computer simulations in underwater acoustic channels indicate that compared with orthogonal wavelet transform super-exponential iterative blind equalization algorithm (WTSEI) and SEI, the convergence rate of this proposed algorithm is faster and the steady-state error is smaller.

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Correspondence to Yecai Guo .

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Guo, Y., Fan, K., Liao, J., Xu, F. (2012). Orthogonal Wavelet Transform Super-Exponential Iterative Blind Equalization Algorithm Based on Optimization of Genetic Algorithm. In: Sambath, S., Zhu, E. (eds) Frontiers in Computer Education. Advances in Intelligent and Soft Computing, vol 133. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27552-4_126

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  • DOI: https://doi.org/10.1007/978-3-642-27552-4_126

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27551-7

  • Online ISBN: 978-3-642-27552-4

  • eBook Packages: EngineeringEngineering (R0)

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