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Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing Based on Endmember Independence and Spatial Weighted Abundance

机译：基于终点独立性和空间加权丰富的高光谱解体稀疏非负矩阵分解

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Jingyan Zhang; Xiangrong Zhang; Licheng Jiao;
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年度 2021
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1. Nonnegative-Matrix-Factorization-Based Hyperspectral Unmixing With Partially Known Endmembers [J] . Lei Tong, Jun Zhou, Yuntao Qian, IEEE Transactions on Geoscience and Remote Sensing . 2016,第11期

机译：基于非负矩阵分解的高光谱与部分已知末端成员的混合
2. Hyperspectral image unmixing algorithm based on endmember-constrained nonnegative matrix factorization [J] . Yan ZHAO, Zhen ZHOU, Donghui WANG, Frontiers of optoelectronics in China . 2016,第4期

机译：基于端元约束非负矩阵分解的高光谱图像分解算法
3. Hyperspectral image unmixing algorithm based on endmember-constrained nonnegative matrix factorization [J] . Yan ZHAO12, Zhen ZHOU1, Donghui WANG3, 中国光电子学前沿：英文版 . 2016,第004期

机译：基于端元约束非负矩阵分解的高光谱图像分解算法
4. Nonnegative matrix factorization with constraints on endmember and abundance for hyperspectral unmixing [C] . Tongxiang Zhi, Bin Yang, Zhao Chen, International Geoscience and Remote Sensing Symposium . 2017

机译：非负矩阵分解，具有对高光谱解混的末端成员和丰度的约束
5. Matrix Factorization: Nonnegativity, Sparsity and Independence. [D] . Potluru, Vamsi Krishna. 2014

机译：矩阵分解：非负性，稀疏性和独立性。
6. Protein Complex Detection via Weighted Ensemble Clustering Based on Bayesian Nonnegative Matrix Factorization [O] . Le Ou-Yang, Dao-Qing Dai, Xiao-Fei Zhang -1

机译：基于贝叶斯非负矩阵分解的加权集成聚类检测蛋白复合物
7. Nonnegative matrix factorization with endmember sparse graph learning for hyperspectral unmixing [O] . Qian Bin, Zhou Jun, Tong Lei, 2016

机译：具有端成员稀疏图学习的非负矩阵分解用于高光谱分解

Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing Based on Endmember Independence and Spatial Weighted Abundance

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