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Cognitive radio today is considered to be the solution to solving the problem of spectrum scarcity. One of the most important features of cognitive radio is spectrum sensing. In spectrum sensing it is sometimes necessary to operate in a low SNR regime, in which the performance of most of the classical detectors decreases, especially when they have to deal with imprecise knowledge of the noise characteristics...
It has been observed that the French electric load series possesses outliers and breaks. Outliers are deviant data points while breaks are lasting abrupt changes in the stochastic pattern of the series. It turns out that outliers and breaks significantly degrade the reliability and accuracy of conventional day-ahead estimation and forecasting methods. Robust methods are needed for this application...
This paper presents a new robust method to estimate the parameters of a SARIMA model. This method uses robust autocorrelations estimates based on sample medians coupled with a robust filter cleaner which rejects deviant observations. Our procedure is compared with other robust methods via evaluation of the different robustness measures such as maximum bias, breakdown point and influence function....
In this paper, the stochastic characteristics of the electric consumption in France are analyzed. It is shown that the load time series exhibit lasting abrupt changes in the stochastic pattern, termed breaks, which need to be accounted for during the modeling process. Thus, a new robust diagnostic approach for which the identification of the breaks is carried out via a robust autocorrelation function...
This paper presents a new robust method to estimate the parameters of ARMA models. This method makes use of the autocorrelations estimates based on the ratio of medians together with a robust filter cleaner able to reject a large fraction of outliers, and a Gaussian maximum likelihood estimation which handles missing values. The main advantages of the procedure are its easiness, robustness and fast...
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