期刊論文     研討會論文     其他著作

• Chia-Hsiang Lin, R. Wu, W.-K. Ma, C.-Y. Chi, and Y. Wang, “Maximum volume inscribed ellipsoid: A new simplex-structured matrix factorization framework via facet enumeration and convex optimization,” SIAM Journal on Imaging Sciences, vol. 11, no. 2, pp. 1651-1679, 2018.
• L. Zhuang, Chia-Hsiang Lin, M. A. T. Figueiredo, and J. M. Bioucas-Dias, “Regularization parameter selection in minimum volume hyperspectral unmixing,” submitted to IEEE Trans. Geoscience and Remote Sensing, 2018.
• Chia-Hsiang Lin, F. Ma, C.-Y. Chi, and C.-H. Hsieh, “A convex optimization based coupled non-negative matrix factorization algorithm for hyperspectral and multispectral data fusion,” IEEE Trans. Geoscience and Remote Sensing, vol. 56, no. 3, pp. 1652-1667, Mar. 2018.

• Chia-Hsiang Lin, C.-Y. Chi, L. Chen, D. J. Miller, and Y. Wang, “Detection of sources in non-negative blind source separation by minimum description length criterion,” accepted as a full paper by IEEE Trans. Neural Networks and Learning Systems, 2017.
• G. Xu, Chia-Hsiang Lin, W. Ma, S. Chen, and C.-Y. Chi, “Outage constrained robust hybrid coordinated beamforming for massive MIMO enabled heterogeneous cellular networks,” IEEE Access, vol. 5, pp. 13601-13616, Mar. 2017.

• Chia-Hsiang Lin, C.-Y. Chi, Y.-H. Wang, and T.-H. Chan, “A fast hyperplane-based minimum-volume enclosing simplex algorithm for blind hyperspectral unmixing,” IEEE Trans. Signal Processing, vol. 64, no. 8, pp. 1946-1961, Apr. 2016.
• A. Ambikapathi, T.-H. Chan, Chia-Hsiang Lin, F.-S. Yang, C.-Y. Chi, and Y. Wang, “Convex optimization-based compartmental pharmacokinetic analysis for prostate tumor characterization using DCE-MRI,” IEEE Trans. Biomedical Engineering, vol. 63, no. 4, pp. 707-720, Apr. 2016.

• Chia-Hsiang Lin, W.-K. Ma, W.-C. Li, C.-Y. Chi, and A. Ambikapathi, “Identifiability of the simplex volume minimization criterion for blind hyperspectral unmixing: The no pure-pixel case,” IEEE Trans. Geoscience and Remote Sensing, vol. 53, no. 10, pp. 5530-5546, Oct. 2015.

• Chia-Hsiang Lin and Jose M. Bioucas-Dias, “Linear spectral unmixing via matrix factorization: Identifiability criteria for sparse abundances,” accepted by IEEE IGARSS, Valencia, Spain, July 23-27, 2018.
• Chia-Hsiang Lin and Jose M. Bioucas-Dias, “Provably and robust blind source separation of ill-conditioned hyperspectral mixtures,” accepted by IEEE SSP, Freiburg, Germany, June 10-13, 2018.
• Chia-Hsiang Lin and Jose M. Bioucas-Dias, “New theory for unmixing ill-conditioned hyperspectral mixtures,” accepted by IEEE SAM, Sheffield, UK, July 8-11, 2018. (Invited Paper)

• G. Xu, Chia-Hsiang Lin, W. Ma, and C.-Y. Chi, “Outage constrained robust hybrid coordinated beamforming for massive MIMO enabled heterogeneous cellular networks,” accepted by IEEE ICC, Paris, France, May 21-25, 2017.

• W.-K. Ma, Chia-Hsiang Lin, W.-C. Li, and C.-Y. Chi, “When can the minimum volume enclosing simplex identify the endmembers correctly when there is no pure pixel?,” in Proc. IEEE WHISPERS, Tokyo, Japan, June 2-5, 2015.
• Chia-Hsiang Lin, C.-Y. Chi, Y.-H. Wang, and T.-H. Chan, “A fast hyperplane-based MVES algorithm for hyperspectral unmixing,” in Proc. IEEE ICASSP, Brisbane, Australia, Apr. 19-24, 2015.

• A. Ambikapathi, T.-H. Chan, Chia-Hsiang Lin, and C.-Y. Chi, “Convex geometry based outlier-insensitive estimation of number of endmembers in hyperspectral images,” in Proc. IEEE WHISPERS, Gainesville, Florida, USA, June 25-28, 2013. (Invited Paper)
• Chia-Hsiang Lin, A. Ambikapathi, W.-C. Li, and C.-Y. Chi, “On the endmember identifiability of Craig’s criterion for hyperspectral unmixing: A statistical analysis for three-source case,” in Proc. IEEE ICASSP, Vancouver, Canada, May 26-31, 2013.

• C.-Y. Chi, W.-C. Li, and Chia-Hsiang Lin, Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications, CRC Press, Boca Raton, FL, Feb. 2017. (Available in CRC Press; also available in Taiwan SCI-TECH.)

研究計畫

年度	計畫名稱	計畫內擔任之工作	委託單位
107	基於凸幾何與大數據優化之前瞻盲蔽訊號源分離與高光譜超解析度成像（五年期「愛因斯坦培植計畫」）	主持人	科技部