Zhong Xiao

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Baseline wander is a common noise in electrocardiogram (ECG) results. To effectively correct the baseline and to preserve more underlying components of an ECG signal, we propose a simple and novel filtering method based on a statistical weighted moving average filter. Supposed a and b are the minimum and maximum of all sample values within a moving window,(More)
In this paper, a novel algorithm was proposed to subtract power line interference (PLI) from contaminated ECG signal. Firstly, some PLI values were calculated from ECG signal in linear segment. Secondly, using nonlinear regression and least squares estimation, sinusoidal parameters such as frequency and phase were estimated from the calculated PLI values.(More)
Baseline wander (BW) is a common noise contaminating electrocardiogram (ECG). In order to effectively correct baseline of ECG signal and to preserve more latent components of ECG signal, this paper proposes a simple and novel filter based on statistically weighted moving average. Firstly, after the arrange between the maximum and the minimum of these(More)
This paper considers the problem of quantization schemes for source localization in wireless sensor networks. First, a channel-aware adaptive quantization scheme for target location estimation is proposed and local sensor nodes dynamically adjust their quantization thresholds according to a kind of position-based information sequences. The scheme(More)
OBJECTIVE To confirm the current major diseases and corresponding pathogens of Codonopsis tangshen in Chongqing. METHODS The main cultivation regions of Codonopsis tangshen in Chongqing were systematically investigated, and the pathogens of the obtained specimens were isolated and identified. RESULTS Totally, five fungal diseases in Codonopsis tangshen(More)
Baseline Wander (BW) is a common noise in electrocardiogram (ECG). To effectively correct and to preserve more underlying components of an ECG signal, a powerful tool for removal of BW noise from various signals was introduced. This paper presented the discrete wavelet to get rid of that noise. This method is based on comparing signal with discrete(More)
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