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This paper describes a newly developed position sensor system. The position sensing system is designed to be combined with the radial permanent magnetic bearing and used for the control of the axial active magnetic bearing. The rotor ring of the radial magnetic bearing is used as field source, which shortens the rotor and saves space for artificial heart design. Linear hall sensor is selected due...
Group delay (GD), the negative derivative of Fourier Transform phase, is regarded as a good tool for spectral estimation in additive noise, for its sharp peak and high resolution. However, as far, GD has not been utilized in the case involving complex noises. In this paper, a novel GD is proposed to the time-varying cumulants of harmonics in complex noises, termed as CGD. A simple and practical algorithm...
Independent component analysis (ICA), both linear and nonlinear, one of the best methods is minimum the mutual information (MI) of the estimated components. Sometimes it is exist many local minima, especially nonlinear mixtures. genetic algorithm (GA) is a method against local minima, and have a high degree of flexibility in the evaluation function. This paper introduce the MI theories, and use MA...
A novel approach for frequency estimation of one-dimensional harmonics in multiplicative and additive noises is presented. To alleviate the resolution limitation of the traditional cumulant-based algorithms, group delay (GD) function is utilized. In this new approach, GD is applied to the 2nd order time-varying cumulants of harmonics in complex noises, called as the 2nd order CGD. For a given frequency...
Generalized Gaussian distribution is a class of symmetry distribution with the Gaussian and Laplacian distribution as the special cases, with delta distribution and uniformity distribution as limit. It is widely applied a great many fields. In this paper, we first deduce the Generalized Gaussian parameter ratio function, and then present a fast parameter estimation of generalized Gaussian distribution;...
Independent component analysis (ICA)/blind source separation (BSS) has received many attentions in neural network and signal processing in recent years. In applications the observed signals are often corrupted with high noise (low SNR, low sample size, non-Gaussian noise), the source number is unknown, and the sources are non-stationary, which are not well correspond to the ideal ICA models and as...
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