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- W2076641274 abstract "Wireless radio channels cause severe distortion in the signals. These distortions can be reduced by using different channel equalization techniques. In this paper, we compare the equalization performance of state-space recursive least squares (SSRLS) and state-space recursive least squares with adaptive memory (SSRLSWAM) to offset the effect of a linear dispersive channel. These adaptive filters are well-suited for the estimation of deterministic signals corrupted by the observation noise. We consider the equalization of both the linear time invariant and linear time varying systems to compare the performance of these filters. The performance is affected by the observation noise variance, choice of the forgetting factor and the model mismatch. We present simulation results to compare these cases by tracking a deterministic signal. It has been shown that SSRLSWAM outperforms SSRLS in both the time invariant and time varying channels." @default.
- W2076641274 created "2016-06-24" @default.
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- W2076641274 date "2013-01-01" @default.
- W2076641274 modified "2023-10-18" @default.
- W2076641274 title "Comparative Analysis of SSRLS and SSRLS with Adaptive Memory for Wireless Channel Equalization" @default.
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- W2076641274 doi "https://doi.org/10.7763/ijfcc.2013.v2.236" @default.
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