本文利用国家气候中心气候系统模式(Beijing climate center climate System Model,BCC_CSM1.1m)提供的1991—2014年海表温度回报数据,将逐步回归模态投影方法(stepwise Pattern Projection Method,SPPM)应用到改进BCC_CSM1.1m模式El N...本文利用国家气候中心气候系统模式(Beijing climate center climate System Model,BCC_CSM1.1m)提供的1991—2014年海表温度回报数据,将逐步回归模态投影方法(stepwise Pattern Projection Method,SPPM)应用到改进BCC_CSM1.1m模式El Nino和南方涛动(ENSO)预报研究。SPPM是一种经验性模式误差订正方法,其主要思路是在大尺度模式预报因子场中找寻出与格点观测预报变量相关性高的信号,通过投影将这种信号反演出来,然后建立回归方程得到订正后的预报结果。本文交叉检验和滚动独立样本检验的结果表明,利用SPPM可以有效地提高BCC_CSM1.1m气候系统模式的预报技巧,尤其是在热带太平洋地区以及印度洋海区,24年交叉检验Nino3.4指数提前6个月预报的相关系数技巧可以提高8%~10%,预报误差得到显著降低。不同季节SPPM订正效果略有不同,其中对秋季的预报技巧提升最为显著。与此同时,交叉检验结果还显示,SPPM对El Nino中心纬向位置的预报也有一定程度的改进。展开更多
Stochastic progressive photon mapping(SPPM)is one of the important global illumination methods in computer graphics.It can simulate caustics and specular-diffuse-specular lighting effects efficiently.However,as a bias...Stochastic progressive photon mapping(SPPM)is one of the important global illumination methods in computer graphics.It can simulate caustics and specular-diffuse-specular lighting effects efficiently.However,as a biased method,it always suffers from both bias and variance with limited iterations,and the bias and the variance bring multi-scale noises into SPPM renderings.Recent learning-based methods have shown great advantages on denoising unbiased Monte Carlo(MC)methods,but have not been leveraged for biased ones.In this paper,we present the first learning-based method specially designed for denoising-biased SPPM renderings.Firstly,to avoid conflicting denoising constraints,the radiance of final images is decomposed into two components:caustic and global.These two components are then denoised separately via a two-network framework.In each network,we employ a novel multi-residual block with two sizes of filters,which significantly improves the model’s capabilities,and makes it more suitable for multi-scale noises on both low-frequency and high-frequency areas.We also present a series of photon-related auxiliary features,to better handle noises while preserving illumination details,especially caustics.Compared with other state-of-the-art learning-based denoising methods that we apply to this problem,our method shows a higher denoising quality,which could efficiently denoise multi-scale noises while keeping sharp illuminations.展开更多
A new ultra-wide band （UWB） modulation scheme called L-ary ultra-wide band time hopping multi-pulse position modulation （UWB-TH-MPPM） is proposed for high data-rate wireless application, which can provide better c...A new ultra-wide band （UWB） modulation scheme called L-ary ultra-wide band time hopping multi-pulse position modulation （UWB-TH-MPPM） is proposed for high data-rate wireless application, which can provide better communication performance. The constant weight code is introduced to construct the MPPM signal and the comparison between MPPM and single pulse position modulation （SPPM） is done in three aspects, namely, power efficiency, bandwidth efficiency, and probability of symbol error, respectively. The theoretical analysis and the numerical results show that when the constant weight code is appropriately chosen, MPPM can achieve lower probability of symbol error and higher power efficiency than SPPM at the cost of more bandwidth under the same condition. The proposed MPPM can be a good candidate in UWB system design.展开更多
基金This work was partially supported by the National Key Research and Development Program of China under Grant No.2017YFB0203000the National Natural Science Foundation of China under Grant Nos.61802187,61872223,and 61702311the Natural Science Foundation of Jiangsu Province of China under Grant No.BK20170857.
文摘Stochastic progressive photon mapping(SPPM)is one of the important global illumination methods in computer graphics.It can simulate caustics and specular-diffuse-specular lighting effects efficiently.However,as a biased method,it always suffers from both bias and variance with limited iterations,and the bias and the variance bring multi-scale noises into SPPM renderings.Recent learning-based methods have shown great advantages on denoising unbiased Monte Carlo(MC)methods,but have not been leveraged for biased ones.In this paper,we present the first learning-based method specially designed for denoising-biased SPPM renderings.Firstly,to avoid conflicting denoising constraints,the radiance of final images is decomposed into two components:caustic and global.These two components are then denoised separately via a two-network framework.In each network,we employ a novel multi-residual block with two sizes of filters,which significantly improves the model’s capabilities,and makes it more suitable for multi-scale noises on both low-frequency and high-frequency areas.We also present a series of photon-related auxiliary features,to better handle noises while preserving illumination details,especially caustics.Compared with other state-of-the-art learning-based denoising methods that we apply to this problem,our method shows a higher denoising quality,which could efficiently denoise multi-scale noises while keeping sharp illuminations.
基金National Natural Science Foundation of China （60271018, 60331010） 0pen Fund of Key Lab of 0ptical Communication and Light-wave Technology （Beijing University of Posts and Telecommunications）, Ministry of Education, China.
文摘A new ultra-wide band （UWB） modulation scheme called L-ary ultra-wide band time hopping multi-pulse position modulation （UWB-TH-MPPM） is proposed for high data-rate wireless application, which can provide better communication performance. The constant weight code is introduced to construct the MPPM signal and the comparison between MPPM and single pulse position modulation （SPPM） is done in three aspects, namely, power efficiency, bandwidth efficiency, and probability of symbol error, respectively. The theoretical analysis and the numerical results show that when the constant weight code is appropriately chosen, MPPM can achieve lower probability of symbol error and higher power efficiency than SPPM at the cost of more bandwidth under the same condition. The proposed MPPM can be a good candidate in UWB system design.
