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A knowledge of phase is important in many situations. Parametric phase estimation methods have certain advantages over nonparametric methods. A method for reconstructing phases in autoregressive (AR) processes using estimated third order cumulant sequences from time-series data is presented.<<ETX>>
The possibility and the construction of a number of fast algorithms for the two-dimensional masking of small mask sizes is clearly demonstrated. These are based on nesting and represent extension of the ideas of Stasinski (1990). Moreover, the authors explain how to make the optimal choice of the algorithm depending on the computational machine available.<<ETX>>
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