Abstract
In this paper, a new blind equalization algorithm based on the feedback neural network is proposed. The feedback is introduced into the neural network to improve control performance, so it can control the step-size variation of blind equalization suitably. That is, the quality of blind equalization is advanced. The structure and state functions of the feedback neural network is provided in this paper. The cost function is proposed, and the iteration formulas of equalization parameters are derived. Results of the simulation verify the effectiveness of the proposed algorithm.
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Zhang, X., Zhang, L. (2011). The Blind Equalization Algorithm Based on the Feedback Neural Network. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_74
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DOI: https://doi.org/10.1007/978-3-642-23887-1_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23886-4
Online ISBN: 978-3-642-23887-1
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