Abstract: The present disclosure relates to a curvature-based signal segmentation method for solar-blind ultraviolet (UV) photodetectors, including the steps of: collecting solar-blind UV radiation using solar-blind UV photodetectors according to a preset sampling time and generating the same into sampled signals; performing noise reduction on the sampled signals to generate filtered signals using a fractional calculus digital filter; calculating estimated curvatures of the filtered signals using a method of circle fitting by discrete points, and numerically optimizing the estimated curvatures using an exponential function to obtain curvature vectors of the filtered signals; and calculating weight coefficients and weighting the filtered signals using a moving average filter function and a binarization method according to the curvature vectors.

Abstract: The present disclosure relates to a curvature-based signal segmentation method for solar-blind ultraviolet (UV) photodetectors, including the steps of: collecting solar-blind UV radiation using solar-blind UV photodetectors according to a preset sampling time and generating the same into sampled signals; performing noise reduction on the sampled signals to generate filtered signals using a fractional calculus digital filter; calculating estimated curvatures of the filtered signals using a method of circle fitting by discrete points, and numerically optimizing the estimated curvatures using an exponential function to obtain curvature vectors of the filtered signals; and calculating weight coefficients and weighting the filtered signals using a moving average filter function and a binarization method according to the curvature vectors.