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Estimation of a Type of Form-Invariant Combined Signals under Autoregressive Operators

Estimation of a Type of Form-Invariant Combined Signals under Autoregressive Operators
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摘要 We focus on a type of combined signals whose forms remain invariant under the autoregressive operators. To extract the true signal from the autoregressive noise, we develop a strategy to separate parameters and use a two-step least squares approach to estimate the autoregressive parameters directly and then further give the estimate of the signal parameters. This method overcomes the difficulty that the autoregressive noise remains unknown in other methods. It can effectively separate the noise and extract the true signal. The algorithm is linear. The solution of the problem is computationally cheap and practical with high accuracy. We focus on a type of combined signals whose forms remain invariant under the autoregressive operators. To extract the true signal from the autoregressive noise, we develop a strategy to separate parameters and use a two-step least squares approach to estimate the autoregressive parameters directly and then further give the estimate of the signal parameters. This method overcomes the difficulty that the autoregressive noise remains unknown in other methods. It can effectively separate the noise and extract the true signal. The algorithm is linear. The solution of the problem is computationally cheap and practical with high accuracy.
出处 《Open Journal of Statistics》 2013年第6期385-389,共5页 统计学期刊(英文)
关键词 Form-Invariant SIGNALS AUTOREGRESSIVE Operator AUTOREGRESSIVE Noise Parameter ESTIMATION Form-Invariant Signals Autoregressive Operator Autoregressive Noise Parameter Estimation
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