A successive cancellation list (SCL) decoder with the assistance of a cyclic redundancy check (CRC) can provide competitive decoding performance for polar codes compared with the state-of-theart codes. In this paper, we adopt a bit-flip algorithm for the CRC-assisted SCL decoder to further improve the error-correcting performance. We first introduce a new bit-flip criterion for the SCL decoder. To support this criterion, we give the metric to identify the positions that need to be flipped. To verify the superiority of the proposed bit-flip criterion, we also consider a kind of SCL-flip decoder whose criterion is very similar with the existing one and we will prove that its performance is worse than the decoder with the proposed bit-flip criterion. The simulation results show that the decoder with the proposed bit-flip criterion outperforms both the standard CRC-assisted SCL decoder and the existing SCL-based bit-flip decoder.
Typical rain gauge measurements have long been recognized to underestimate actual precipitation. Long-term daily precipitation records during 1961–2013 from a dense national network of 2379 gauges were corrected to remove systematic errors caused by trace precipitation, wetting losses, and wind-induced undercatch. The corrected percentage was higher in cold seasons and lower in warm seasons. Both trace precipitation and wetting loss corrections were more important in arid regions than in wet regions. A greater correction percentage for wind-induced error could be found in cold and arid regions, as well as high wind speed areas. Generally, the annual precipitation amounts as well as the annual precipitation intensity increased to varying degrees after bias correction with the maximum percentage being about 35%. More importantly, the bias-corrected snowfall amount as well as the rainstorm amount increased remarkably by percentages of more than 50% and 18%, respectively. Remarkably, the total number of actual rainstorm events during the past 53 years could be 90 days more than the observed rainstorm events in some coastal areas of China. Therefore, the actual amounts of precipitation, snowfall, and intense rainfall were much higher than previously measured over China. Bias correction is thus needed to obtain accurate estimates of precipitation amounts and precipitation intensity.
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