Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Digital processing of random signals: theory and methods
Digital processing of random signals: theory and methods
Digital Signal Processing Handbook
Digital Signal Processing Handbook
Time-Frequency Analysis: Concepts and Methods
Time-Frequency Analysis: Concepts and Methods
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This paper deals with a method for the estimation of the signal cyclic component's period using an autoregressive model. The application to economic time series is presented on the example of the index of industrial production data for EU countries. As the economic time series are usually relatively short, the properties of the method are explored and quantified in the case of its application to short sample size signals. A number of computer experiments has been performed using the harmonic signal corrupted by noise and the autoregressive model of the second order. The results of the experiments are represented in the graphical form. It could be noticed that the mean value of the errors could result to significant values while the variance of the error is generally almost negligible. The difference between the spectrum estimation from the whole data differs from the case of using the sliding window spectrum estimation.