Abstract
Novel algorithms of fading Kalman filter (FF) are studied and described for optimal state/parameter estimation, multicomponent analysis and peak resolutions. FF is the modified algorithm by introducing the fading factors to the classical Kalman filter(CF). The specific virtues and some defects of these approaches are evaluated and discussed. FF can be used to obtain the convergenced estimation faster than CF. The main demerit is that the estimation is slightly less accurate than that of CF. This situation can be improved by selecting the better fading factors, for instance, by using the optimal adaptive fading factors.
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