Tree-based models for random distribution of mass

A mathematical model for distribution of mass ind-dimensional space, based upon randomly embedding random trees into space, is introduced and studied. The model is a variant of thesuper Brownian motion process studied by mathematicians. We present calculations relating to (i) the distribution of position of a typical mass element, (ii) moments of the center of mass, (iii) large-deviation behavior, and (iv) a recursive self-similarity property.     

1550 nm飞秒脉冲自相似光纤放大仿真模拟EI北大核心CSCD

针对全光纤的超短脉冲掺铒光纤放大器进行了仿真模拟,对正常色散条件下掺铒光纤自相似脉冲放大过程进行了详细分析。在光纤预放大器中,使用高正色散掺铒光纤对脉冲形状进行预整形,将重复频率43 MHz、脉冲宽度600 fs、平均输出功率1.2 mW的孤子型锁模脉冲预整形为抛物线型脉冲,预整形后的脉冲通过光纤主放大器进行功率放大。经两级光纤放大后,1.2 mW的信号光功率放大为102 mW,放大增益19.3 dB。分析了掺铒光纤长度、放大功率对脉冲自相似演化过程的影响。放大后的脉冲经4.4 m长单模光纤将脉冲宽度压缩至53 fs,峰值功率为44.8 kW。     

Structural similarity based single image super-resolution with nonlocal regularization

Recently, sparse coding based image super-resolution has attracted increasing interests. This paper proposes an improved image super-resolution method, by incorporating structural similarity (SSIM) index and nonlocal regularization into the framework of image super-resolution via sparse coding. Firstly, an algorithm of combining SSIM based sparse coding and K-SVD is proposed to train the high resolution (HR) and low resolution (LR) dictionary pairs. And then, the sparse representations of observed LR image are sought to reconstruct the HR image with the trained LR and HR dictionary pairs by exploiting nonlocal self-similarities. Experimental results demonstrate the effectiveness of the proposed method, both in its visual effects and in quantitative terms.