A new watermarking scheme using principal component analysis (PCA) is described.The proposed method inserts highly robust watermarks into still images without degrading their visual quality. Experimental results are p...A new watermarking scheme using principal component analysis (PCA) is described.The proposed method inserts highly robust watermarks into still images without degrading their visual quality. Experimental results are presented, showing that the PCA based watermarks can resist malicious attacks including lowpass filtering, re scaling, and compression coding.展开更多
Monte Carlo and quasi-Monte Carlomethods arewidely used in scientific studies.As quasi-Monte Carlo simulations have advantage over ordinaryMonte Carlomethods,this paper proposes a new quasi-Monte Carlo method to simul...Monte Carlo and quasi-Monte Carlomethods arewidely used in scientific studies.As quasi-Monte Carlo simulations have advantage over ordinaryMonte Carlomethods,this paper proposes a new quasi-Monte Carlo method to simulate Brownian sheet via its Karhunen–Loéve expansion.The proposed new approach allocates quasi-random sequences for the simulation of random components of the Karhunen–Loéve expansion by maximum reducing its variability.We apply the quasi-MonteCarlo approach to an option pricing problem for a class of interest rate models whose instantaneous forward rate driven by a different stochastic shock through Brownian sheet andwe demonstrate the application with an empirical problem.展开更多
文摘A new watermarking scheme using principal component analysis (PCA) is described.The proposed method inserts highly robust watermarks into still images without degrading their visual quality. Experimental results are presented, showing that the PCA based watermarks can resist malicious attacks including lowpass filtering, re scaling, and compression coding.
文摘在合成孔径雷达(Synthetic Aperture Radar,SAR)成像中,当方位向合成孔径较大时,观测区域内目标的电磁特征会表现为各向异性,导致基于各向同性假设的传统SAR成像方法不再适用。为此,宽角SAR成像方法通过将宽孔径划分为多个子孔径,利用每个子孔径对应的回波数据单独成像,实现对目标雷达图像的多角度重构。由于目标的散射特性在相邻子孔径中通常不会发生较大改变,每个子孔径的强散射中心分布高度相似,使得宽角SAR的成像结果具有低秩结构,即相邻子孔径对应的目标成像结果的支撑集相近。为了使用这种相关性,将Karhunen Loeve(KL)变换引入到宽角SAR成像过程中,再利用目标强散射中心分布的稀疏特性,建立基于低秩结构的宽角SAR稀疏成像模型。采用增广拉格朗日法(Augmented Lagrangian,AL)和交替方向乘子(Alternating Direction Method of Multipliers,ADMM)对上述成像模型进行迭代求解,从而获得宽角SAR成像结果。相比于传统的宽角SAR成像方法,本文所述方法不仅能提高目标后向散射系数的重建精度,还能有效抑制旁瓣效应与信号噪声对成像质量的影响,对目标电磁特征的多角度恢复具有更好的效果。
基金The research of Yazhen Wang was supported in part by NSF[grant number DMS-12-65203][grant number DMS-15-28375].
文摘Monte Carlo and quasi-Monte Carlomethods arewidely used in scientific studies.As quasi-Monte Carlo simulations have advantage over ordinaryMonte Carlomethods,this paper proposes a new quasi-Monte Carlo method to simulate Brownian sheet via its Karhunen–Loéve expansion.The proposed new approach allocates quasi-random sequences for the simulation of random components of the Karhunen–Loéve expansion by maximum reducing its variability.We apply the quasi-MonteCarlo approach to an option pricing problem for a class of interest rate models whose instantaneous forward rate driven by a different stochastic shock through Brownian sheet andwe demonstrate the application with an empirical problem.
