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Abstract. Denoising is very important in signal processing. Electrocardiogram (ECG) data always contains 50 or 60 Hz power line interferences (PLI), PLI may affect the detection of P wave, QRS complex and T wave. So the pre-processing of ECG data is necessary. In order to remove PLI, in this paper, we use two improved tracking-differentiator filters (ITDFs), which are signed ITDF1 and ITDF2 respectively. The simulation results for ECG signals obtained from MIT-BIH database indicate that ITDFs are good methods for filtering noises, and ITDF2 does better than ITDF1.

Parameter estimation is an important step in the identification of systems. With the extension of systems, there needs the multi-parameter estimation of systems. The estimation of multi parameters of complex systems based on the extended PID controllers is considered in this chapter. As the related references proved that the integral item of the nonlinear PID controller could deal with the uncertain part of the complex system (which can also be called new stripping principle, simple notes as NSP). Based on this theory, new multi-parameter estimation method is given. Firstly, the unknown parameters are expanded to new states of the system. Two cases, parameters are constant or changing with time, are separately analyzed. In the time-variant case, the unknown parameters are extended to functions which actual forms are uncertain. Secondly the method NSP could be applied to cope with the uncertain part, and then reconstruction state observation to estimate the states. If the states are observed, the unknown parameters are obtained at the same time. Finally the convergence analysis of the error systems and some simulations will be given in this chapter to indicate the effectiveness of the proposed method.