Abstract
The structural complexity and overall performance of the adaptive filter depend on its structure. The number of taps is one of the most important structural parameters of the liner adaptive filter. In practice the system length is not known a-priori and has to be estimated from the knowledge of the input and output signals. In a system identification framework the tap length estimation algorithm automatically adapts the filter order to the desired optimum value which makes the variable order adaptive filter a best identifier of the unknown plant. In this paper an improved pseudo-fractional tap-length selection algorithm has been proposed to find out the optimum tap-length which best balances the complexity and steady state performance. Simulation results reveal that the proposed algorithm results in reduced complexity and faster convergence in comparison to existing tap-length learning methods.
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© 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Kar, A., Chandra, M. (2013). Reduced Complexity Pseudo-fractional Adaptive Algorithm with Variable Tap-Length Selection. In: Singh, K., Awasthi, A.K. (eds) Quality, Reliability, Security and Robustness in Heterogeneous Networks. QShine 2013. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37949-9_39
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DOI: https://doi.org/10.1007/978-3-642-37949-9_39
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