In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused...In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused byαparticle ionizing radiation was proposed,and the effects of dead-pixel compensation algorithms were compared and analyzed under different parameter conditions.The experimental results show thatαparticle response signal has highest accuracy at 9 dB gain,with an obvious“target-ring”distribution.With increasing cumulative dose,the CMOS APS pedestal tends to saturation while dead pixels continue increasing.Though some pixel damage recovers through natural annealing,the dead-to-noise ratio increases with irradiation time,reaching 32.54%after 72 h.A hierarchical clustering dead-pixel detection method is proposed,categorizing pixels into two types:those within and outside the response event.A classification compensation strategy combining mean and majority filtering is proposed.This compensation algorithm can address dead-pixel interference without affectingαparticle radiation response data.When iterated multiple times and with integration time exceeding 6.31 ms,the number of dead pixels can be effectively reduced.展开更多
In this work a Support Vector Machine Regression（SVMR） algorithm is used to calculate local magnitude（MI） using only five seconds of signal after the P wave onset of one three component seismic station. This algor...In this work a Support Vector Machine Regression（SVMR） algorithm is used to calculate local magnitude（MI） using only five seconds of signal after the P wave onset of one three component seismic station. This algorithm was trained with 863 records of historical earthquakes, where the input regression parameters were an exponential function of the waveform envelope estimated by least squares and the maximum value of the observed waveform for each component in a single station. Ten-fold cross validation was applied for a normalized polynomial kernel obtaining the mean absolute error for different exponents and complexity parameters. The local magnitude（MI） could be estimated with 0.19 units of mean absolute error. The proposed algorithm is easy to implement in hardware and may be used directly after the field seismological sensor to generate fast decisions at seismological control centers, increasing the possibility of having an effective reaction.展开更多
基金supported by the National Natural Science Foundation of China(No.11905102)Hunan Provincial Postgraduate Research and Innovation Project(No.QL20230234)。
文摘In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused byαparticle ionizing radiation was proposed,and the effects of dead-pixel compensation algorithms were compared and analyzed under different parameter conditions.The experimental results show thatαparticle response signal has highest accuracy at 9 dB gain,with an obvious“target-ring”distribution.With increasing cumulative dose,the CMOS APS pedestal tends to saturation while dead pixels continue increasing.Though some pixel damage recovers through natural annealing,the dead-to-noise ratio increases with irradiation time,reaching 32.54%after 72 h.A hierarchical clustering dead-pixel detection method is proposed,categorizing pixels into two types:those within and outside the response event.A classification compensation strategy combining mean and majority filtering is proposed.This compensation algorithm can address dead-pixel interference without affectingαparticle radiation response data.When iterated multiple times and with integration time exceeding 6.31 ms,the number of dead pixels can be effectively reduced.
文摘In this work a Support Vector Machine Regression（SVMR） algorithm is used to calculate local magnitude（MI） using only five seconds of signal after the P wave onset of one three component seismic station. This algorithm was trained with 863 records of historical earthquakes, where the input regression parameters were an exponential function of the waveform envelope estimated by least squares and the maximum value of the observed waveform for each component in a single station. Ten-fold cross validation was applied for a normalized polynomial kernel obtaining the mean absolute error for different exponents and complexity parameters. The local magnitude（MI） could be estimated with 0.19 units of mean absolute error. The proposed algorithm is easy to implement in hardware and may be used directly after the field seismological sensor to generate fast decisions at seismological control centers, increasing the possibility of having an effective reaction.
