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Strong law of large numbers is a fundamental theory in probability and statistics. When the measure tool is nonadditive, this law is very different from additive case. In 2010 Chen investigated the strong law of large numbers under upper probabilityVby assumingVis continuous. This assumption is very strong. Upper probabilities may not be continuous. In this paper we prove the strong law of large numbers for an upper probability without the continuity assumption whereby random variables are quasi-continuous and the upper probability is generated by a weakly compact family of probabilities on a complete and separable metric sample space.
Because of the illposedness of soft field, the
quality of EIT images is not satisfied as expected. This paper puts forward a
threshold strategy to decrease the artifacts in the reconstructed images by
modifying the solutions of inverse problem. Threshold strategy is a kind of
post processing method with merits of easy, direct and efficient. Reconstructed
by Gauss-Newton algorithm, the simulation image’s quality is improved
evidently. We take two performance targets, image reconstruction error and
correlation coefficient, to evaluate the improvement. The images and the data
show that threshold strategy is effective and achievable.
A digital biomedical electrical impedance tomography
(EIT) system is developed with the aid of FPGA. The key elements of EIT system
are described specifically in the paper. The functions are realized to generate
excitation source, switch electrode channels, deal collected signals,
demodulate measured voltages etc. The system is tested by a circular tank with
16 stainless electrodes attached around the boundary. The adjacent incentive
adjacent measurement mode is adapted to collect boundary voltages of the interesting
field. By testing, the system works with 36 dB signal-to-noise ratio (SNR) when
1 mA 100 KHz current is applied into a homogenous tank.