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机译:大型L0-范数和L1-范数2-D相展开
Department of Civil and Environmental Engineering, University of Houston, Houston, TX, USA;
National Lab of Radar Signal Processing, Xidian University, Xi’an, China;
Xi’an Information Technique Institute of Surveying and Mapping, Xi’an, China;
National University of Defense Technology, Changsha, China;
Department of Civil and Environmental Engineering, University of Houston, Houston, TX, USA;
Memory management; Spatial resolution; Optimization; Synthetic aperture radar interferometry; Hardware; Laser radar; Laser theory;
机译:使用最小无穷范的二维相位展开
机译:通过L1 L1和L0 L0-NOM-NOM-NOM-NOM-NOM-NOM-NOM罚款的组稀疏SVD模型及其在生物数据中的应用
机译:使用Huber-norm改进了在存在相位展开错误的情况下的DInSAR时间序列重构
机译:基于混合l0 / l1规范最小化的图像着色
机译:二维相位展开研究。
机译:基于稀疏表示的直接最小LMRI相位展开的p-范数算法
机译:通过调整平滑L0算法超越压缩感知中的理论1范数相变
机译:具有全局线性收敛算法的增广l1和核范数模型。修订版1。