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X. Ma, Z. Wang, Y. Li, G. R. Arce, L. Dong, and J. G. Frias, “Fast optical proximity correction method based on nonlinear compressive sensing,” Opt. Express 26(11), 14479–14498 (2018).

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X. Ma, D. Shi, Z. Wang, Y. Li, and G. R. Arce, “Lithographic source optimization based on adaptive projection compressive sensing,” Opt. Express 25(6), 7131–7149 (2017).

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H. You, Z. Ma, W. Li, and J. Zhu, “A speech enhancement method based on multi-task Bayesian compressive sensing,” IEICE Tran. Inf. & Syst. E100.D(3), 556–563 (2017).

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X. Gu, P. Zhou, and X. Gu, “Bayesian compressive sensing for thermal imagery using Gaussian-Jeffreys prior,” Infrared Phys. Techn. 83, 51–61 (2017).

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K. Huang, S. Tan, Y. Luo, X. Guo, and G. Wang, “Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing,” Pervasive and Mobile Computing 40, 450–463 (2017).

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Z. Song, X. Ma, J. Gao, J. Wang, Y. Li, and G. R. Arce, “Inverse lithography source optimization via compressive sensing,” Opt. Express 22(12), 14180–14198 (2014).

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Z. Zhang, T. Jung, S. Makeig, and B. D. Rao, “Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning,” IEEE Trans. Biomed. Eng. 60(2), 300–309 (2013).

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X. Ma, C. Han, Y. Li, L. Dong, and G. R. Arce, “Pixelated source and mask optimization for immersion lithography,” J. Opt. Soc. Am. A 30(1), 112–123 (2013).

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K. Iwase, P. D. Bisschop, B. Laenens, Z. Li, K. Gronlund, P. V. Adrichem, and S. Hsu, “A new source optimization approach for 2x node logic,” Proc. SPIE 8166, 81662A (2011).

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[Crossref]

X. Ma, Z. Wang, H. Lin, Y. Li, G. R. Arce, and L. Zhang, “Optimization of lithography source illumination arrays using diffraction subspaces,” Opt. Express 26(4), 3738–3755 (2018).

[Crossref]

X. Ma, Z. Wang, Y. Li, G. R. Arce, L. Dong, and J. G. Frias, “Fast optical proximity correction method based on nonlinear compressive sensing,” Opt. Express 26(11), 14479–14498 (2018).

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X. Ma, L. Dong, C. Han, J. Gao, Y. Li, and G. R. Arce, “Gradient-based joint source polarization mask optimization for optical lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 14(2), 023504 (2015).

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X. Ma, C. Han, Y. Li, L. Dong, and G. R. Arce, “Pixelated source and mask optimization for immersion lithography,” J. Opt. Soc. Am. A 30(1), 112–123 (2013).

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X. Ma and G. R. Arce, “Pixel-based simultaneous source and mask optimization for resolution enhancement in optical lithography,” Opt. Express 17(7), 5783–5793 (2009).

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Y. V. Miklyaev, W. Imgrunt, V. S. Pavelyev, D. G. Kachalov, T. Bizjak, L. Aschke, and V. N. Lissotschenko, “Novel continuously shaped diffractive optical elements enable high-efficiency beam shaping,” Proc. SPIE 7640, 764024 (2010).

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[Crossref]

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J. T. Carriere, J. Stack, A. D. Kathman, and M. D. Himel, “Advances in DOE modeling and optical performance for SMO applications in immersion lithography at the 32 nm node and beyond,” Proc. SPIE 7640, 764025 (2010).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

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[Crossref]

X. Ma, L. Dong, C. Han, J. Gao, Y. Li, and G. R. Arce, “Gradient-based joint source polarization mask optimization for optical lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 14(2), 023504 (2015).

[Crossref]

X. Guo, Y. Li, L. Dong, L. Liu, X. Ma, and C. Han, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 13(4), 043013 (2014).

[Crossref]

X. Ma, C. Han, Y. Li, L. Dong, and G. R. Arce, “Pixelated source and mask optimization for immersion lithography,” J. Opt. Soc. Am. A 30(1), 112–123 (2013).

[Crossref]

X. Ma, Y. Li, X. Guo, and L. Dong, “Vectorial mask optimization method for robust optical lithography,” J. Micro/Nanolith. MESM. MOEMS. 11(4), 043008 (2012).

[Crossref]

X. Ma, Y. Li, and L. Dong, “Mask optimization approaches in optical lithography based on a vector imaging model,” J. Opt. Soc. Am. A 29(7), 1300–1312 (2012).

[Crossref]

D. Donoho, “Compressive sensing,” IEEE Trans. Inf. Theory 52(4), 1289–1306 (2006).

[Crossref]

A. Erdmann, T. Fühner, T. Schnattinger, and B. Tollkühn, “Towards automatic mask and source optimization for optical lithography,” Proc. SPIE 5377, 646–657 (2004).

[Crossref]

A. E. Rosenbluth, S. Bukofsky, C. Fonseca, M. Hibbs, K. Lai, A. Molless, R. N. Singh, and A. K. Wong, “Optimum mask and source patterns to print a given shape,” J. Microlith. Microfab. 1(1), 486 (2002).

[Crossref]

A. Erdmann, T. Fühner, T. Schnattinger, and B. Tollkühn, “Towards automatic mask and source optimization for optical lithography,” Proc. SPIE 5377, 646–657 (2004).

[Crossref]

X. Ma, L. Dong, C. Han, J. Gao, Y. Li, and G. R. Arce, “Gradient-based joint source polarization mask optimization for optical lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 14(2), 023504 (2015).

[Crossref]

Z. Song, X. Ma, J. Gao, J. Wang, Y. Li, and G. R. Arce, “Inverse lithography source optimization via compressive sensing,” Opt. Express 22(12), 14180–14198 (2014).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

[Crossref]

Y. Granik, “Source optimization for image fidelity and throughput,” J. Microlith. Microfab. 3(4), 509–522 (2004).

K. Iwase, P. D. Bisschop, B. Laenens, Z. Li, K. Gronlund, P. V. Adrichem, and S. Hsu, “A new source optimization approach for 2x node logic,” Proc. SPIE 8166, 81662A (2011).

[Crossref]

X. Gu, P. Zhou, and X. Gu, “Bayesian compressive sensing for thermal imagery using Gaussian-Jeffreys prior,” Infrared Phys. Techn. 83, 51–61 (2017).

[Crossref]

X. Gu, P. Zhou, and X. Gu, “Bayesian compressive sensing for thermal imagery using Gaussian-Jeffreys prior,” Infrared Phys. Techn. 83, 51–61 (2017).

[Crossref]

K. Huang, S. Tan, Y. Luo, X. Guo, and G. Wang, “Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing,” Pervasive and Mobile Computing 40, 450–463 (2017).

[Crossref]

X. Guo, Y. Li, L. Dong, L. Liu, X. Ma, and C. Han, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 13(4), 043013 (2014).

[Crossref]

X. Ma, Y. Li, X. Guo, and L. Dong, “Vectorial mask optimization method for robust optical lithography,” J. Micro/Nanolith. MESM. MOEMS. 11(4), 043008 (2012).

[Crossref]

X. Ma, L. Dong, C. Han, J. Gao, Y. Li, and G. R. Arce, “Gradient-based joint source polarization mask optimization for optical lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 14(2), 023504 (2015).

[Crossref]

C. Han, Y. Li, X. Ma, and L. Liu, “Robust hybrid source and mask optimization to lithography source blur and flare,” Appl. Opt. 54(17), 5291–5302 (2015).

[Crossref]

X. Guo, Y. Li, L. Dong, L. Liu, X. Ma, and C. Han, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 13(4), 043013 (2014).

[Crossref]

X. Ma, C. Han, Y. Li, L. Dong, and G. R. Arce, “Pixelated source and mask optimization for immersion lithography,” J. Opt. Soc. Am. A 30(1), 112–123 (2013).

[Crossref]

S. G. Hansen, “Source mask polarization optimization,” J. Micro/Nanolithogr., MEMS, MOEMS 10(3), 033003 (2011).

[Crossref]

A. E. Rosenbluth, S. Bukofsky, C. Fonseca, M. Hibbs, K. Lai, A. Molless, R. N. Singh, and A. K. Wong, “Optimum mask and source patterns to print a given shape,” J. Microlith. Microfab. 1(1), 486 (2002).

[Crossref]

J. T. Carriere, J. Stack, A. D. Kathman, and M. D. Himel, “Advances in DOE modeling and optical performance for SMO applications in immersion lithography at the 32 nm node and beyond,” Proc. SPIE 7640, 764025 (2010).

[Crossref]

K. Iwase, P. D. Bisschop, B. Laenens, Z. Li, K. Gronlund, P. V. Adrichem, and S. Hsu, “A new source optimization approach for 2x node logic,” Proc. SPIE 8166, 81662A (2011).

[Crossref]

K. Huang, S. Tan, Y. Luo, X. Guo, and G. Wang, “Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing,” Pervasive and Mobile Computing 40, 450–463 (2017).

[Crossref]

Y. V. Miklyaev, W. Imgrunt, V. S. Pavelyev, D. G. Kachalov, T. Bizjak, L. Aschke, and V. N. Lissotschenko, “Novel continuously shaped diffractive optical elements enable high-efficiency beam shaping,” Proc. SPIE 7640, 764024 (2010).

[Crossref]

K. Iwase, P. D. Bisschop, B. Laenens, Z. Li, K. Gronlund, P. V. Adrichem, and S. Hsu, “A new source optimization approach for 2x node logic,” Proc. SPIE 8166, 81662A (2011).

[Crossref]

S. Ji, Y. Xue, and L. Carin, “Bayesian compressive sensing,” IEEE T. Signal Proces. 56(6), 2346–2356 (2008).

[Crossref]

H. Jiang and T. Xing, “A method of source optimization to maximize process window,” Laser Optoelectron. Prog. 52(10), 101101 (2015).

[Crossref]

J. Wu, F. Liu, L. Jiao, and X. Wang, “Compressive sensing SAR image reconstruction based on Bayesian framework and evolutionary computation,” IEEE T. Image Proces. 20(7), 1904–1911 (2011).

[Crossref]

Z. Zhang, T. Jung, S. Makeig, and B. D. Rao, “Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning,” IEEE Trans. Biomed. Eng. 60(2), 300–309 (2013).

[Crossref]

Y. V. Miklyaev, W. Imgrunt, V. S. Pavelyev, D. G. Kachalov, T. Bizjak, L. Aschke, and V. N. Lissotschenko, “Novel continuously shaped diffractive optical elements enable high-efficiency beam shaping,” Proc. SPIE 7640, 764024 (2010).

[Crossref]

J. T. Carriere, J. Stack, A. D. Kathman, and M. D. Himel, “Advances in DOE modeling and optical performance for SMO applications in immersion lithography at the 32 nm node and beyond,” Proc. SPIE 7640, 764025 (2010).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

[Crossref]

K. Iwase, P. D. Bisschop, B. Laenens, Z. Li, K. Gronlund, P. V. Adrichem, and S. Hsu, “A new source optimization approach for 2x node logic,” Proc. SPIE 8166, 81662A (2011).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

[Crossref]

A. E. Rosenbluth, S. Bukofsky, C. Fonseca, M. Hibbs, K. Lai, A. Molless, R. N. Singh, and A. K. Wong, “Optimum mask and source patterns to print a given shape,” J. Microlith. Microfab. 1(1), 486 (2002).

[Crossref]

J. Li, S. Liu, and E. Y. Lam, “Efficient source and mask optimization with augumented Lagrangian methods in optical lithography,” Opt. Express 21(7), 8076–8090 (2013).

[Crossref]

J. Li, Y. Shen, and E. Y. Lam, “Hotspot-aware fast source and mask optimization,” Opt. Express 20(19), 21792–21804 (2012).

[Crossref]

J. Li, S. Liu, and E. Y. Lam, “Efficient source and mask optimization with augumented Lagrangian methods in optical lithography,” Opt. Express 21(7), 8076–8090 (2013).

[Crossref]

J. Li, Y. Shen, and E. Y. Lam, “Hotspot-aware fast source and mask optimization,” Opt. Express 20(19), 21792–21804 (2012).

[Crossref]

L. Wang, S. Li, X. Wang, G. Yan, and C. Yang, “Source optimization using particle swarm optimization algorithm in optical lithography,” Acta Opt. Sin. 35(4), 0422002 (2015).

[Crossref]

Y. Sun, N. Sheng, T. Li, Y. Li, E. Li, and P. Wei, “Fast nonlinear compressive sensing lithographic source and mask optimization method using Newton-IHTs algorithm,” Opt. Express 27(3), 2754–2770 (2019).

[Crossref]

T. Li and Y. Li, “Lithographic source and mask optimization with low aberration sensitivity,” IEEE Trans. Nanotechnol. 16(6), 1099–1105 (2017).

[Crossref]

H. You, Z. Ma, W. Li, and J. Zhu, “A speech enhancement method based on multi-task Bayesian compressive sensing,” IEICE Tran. Inf. & Syst. E100.D(3), 556–563 (2017).

[Crossref]

Y. Sun, N. Sheng, T. Li, Y. Li, E. Li, and P. Wei, “Fast nonlinear compressive sensing lithographic source and mask optimization method using Newton-IHTs algorithm,” Opt. Express 27(3), 2754–2770 (2019).

[Crossref]

X. Ma, Z. Wang, H. Lin, Y. Li, G. R. Arce, and L. Zhang, “Optimization of lithography source illumination arrays using diffraction subspaces,” Opt. Express 26(4), 3738–3755 (2018).

[Crossref]

X. Ma, Z. Wang, Y. Li, G. R. Arce, L. Dong, and J. G. Frias, “Fast optical proximity correction method based on nonlinear compressive sensing,” Opt. Express 26(11), 14479–14498 (2018).

[Crossref]

X. Ma, D. Shi, Z. Wang, Y. Li, and G. R. Arce, “Lithographic source optimization based on adaptive projection compressive sensing,” Opt. Express 25(6), 7131–7149 (2017).

[Crossref]

T. Li and Y. Li, “Lithographic source and mask optimization with low aberration sensitivity,” IEEE Trans. Nanotechnol. 16(6), 1099–1105 (2017).

[Crossref]

C. Han, Y. Li, X. Ma, and L. Liu, “Robust hybrid source and mask optimization to lithography source blur and flare,” Appl. Opt. 54(17), 5291–5302 (2015).

[Crossref]

X. Ma, L. Dong, C. Han, J. Gao, Y. Li, and G. R. Arce, “Gradient-based joint source polarization mask optimization for optical lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 14(2), 023504 (2015).

[Crossref]

X. Guo, Y. Li, L. Dong, L. Liu, X. Ma, and C. Han, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 13(4), 043013 (2014).

[Crossref]

Z. Song, X. Ma, J. Gao, J. Wang, Y. Li, and G. R. Arce, “Inverse lithography source optimization via compressive sensing,” Opt. Express 22(12), 14180–14198 (2014).

[Crossref]

X. Ma, C. Han, Y. Li, L. Dong, and G. R. Arce, “Pixelated source and mask optimization for immersion lithography,” J. Opt. Soc. Am. A 30(1), 112–123 (2013).

[Crossref]

X. Ma, Y. Li, and L. Dong, “Mask optimization approaches in optical lithography based on a vector imaging model,” J. Opt. Soc. Am. A 29(7), 1300–1312 (2012).

[Crossref]

X. Ma, Y. Li, X. Guo, and L. Dong, “Vectorial mask optimization method for robust optical lithography,” J. Micro/Nanolith. MESM. MOEMS. 11(4), 043008 (2012).

[Crossref]

K. Iwase, P. D. Bisschop, B. Laenens, Z. Li, K. Gronlund, P. V. Adrichem, and S. Hsu, “A new source optimization approach for 2x node logic,” Proc. SPIE 8166, 81662A (2011).

[Crossref]

Y. V. Miklyaev, W. Imgrunt, V. S. Pavelyev, D. G. Kachalov, T. Bizjak, L. Aschke, and V. N. Lissotschenko, “Novel continuously shaped diffractive optical elements enable high-efficiency beam shaping,” Proc. SPIE 7640, 764024 (2010).

[Crossref]

J. Wu, F. Liu, L. Jiao, and X. Wang, “Compressive sensing SAR image reconstruction based on Bayesian framework and evolutionary computation,” IEEE T. Image Proces. 20(7), 1904–1911 (2011).

[Crossref]

C. Han, Y. Li, X. Ma, and L. Liu, “Robust hybrid source and mask optimization to lithography source blur and flare,” Appl. Opt. 54(17), 5291–5302 (2015).

[Crossref]

X. Guo, Y. Li, L. Dong, L. Liu, X. Ma, and C. Han, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 13(4), 043013 (2014).

[Crossref]

K. Huang, S. Tan, Y. Luo, X. Guo, and G. Wang, “Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing,” Pervasive and Mobile Computing 40, 450–463 (2017).

[Crossref]

X. Ma, Z. Wang, Y. Li, G. R. Arce, L. Dong, and J. G. Frias, “Fast optical proximity correction method based on nonlinear compressive sensing,” Opt. Express 26(11), 14479–14498 (2018).

[Crossref]

X. Ma, Z. Wang, H. Lin, Y. Li, G. R. Arce, and L. Zhang, “Optimization of lithography source illumination arrays using diffraction subspaces,” Opt. Express 26(4), 3738–3755 (2018).

[Crossref]

X. Ma, D. Shi, Z. Wang, Y. Li, and G. R. Arce, “Lithographic source optimization based on adaptive projection compressive sensing,” Opt. Express 25(6), 7131–7149 (2017).

[Crossref]

X. Ma, L. Dong, C. Han, J. Gao, Y. Li, and G. R. Arce, “Gradient-based joint source polarization mask optimization for optical lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 14(2), 023504 (2015).

[Crossref]

C. Han, Y. Li, X. Ma, and L. Liu, “Robust hybrid source and mask optimization to lithography source blur and flare,” Appl. Opt. 54(17), 5291–5302 (2015).

[Crossref]

X. Guo, Y. Li, L. Dong, L. Liu, X. Ma, and C. Han, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 13(4), 043013 (2014).

[Crossref]

Z. Song, X. Ma, J. Gao, J. Wang, Y. Li, and G. R. Arce, “Inverse lithography source optimization via compressive sensing,” Opt. Express 22(12), 14180–14198 (2014).

[Crossref]

X. Ma, C. Han, Y. Li, L. Dong, and G. R. Arce, “Pixelated source and mask optimization for immersion lithography,” J. Opt. Soc. Am. A 30(1), 112–123 (2013).

[Crossref]

X. Ma, Y. Li, and L. Dong, “Mask optimization approaches in optical lithography based on a vector imaging model,” J. Opt. Soc. Am. A 29(7), 1300–1312 (2012).

[Crossref]

X. Ma, Y. Li, X. Guo, and L. Dong, “Vectorial mask optimization method for robust optical lithography,” J. Micro/Nanolith. MESM. MOEMS. 11(4), 043008 (2012).

[Crossref]

X. Ma and G. R. Arce, “Pixel-based simultaneous source and mask optimization for resolution enhancement in optical lithography,” Opt. Express 17(7), 5783–5793 (2009).

[Crossref]

H. You, Z. Ma, W. Li, and J. Zhu, “A speech enhancement method based on multi-task Bayesian compressive sensing,” IEICE Tran. Inf. & Syst. E100.D(3), 556–563 (2017).

[Crossref]

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[Crossref]

Y. V. Miklyaev, W. Imgrunt, V. S. Pavelyev, D. G. Kachalov, T. Bizjak, L. Aschke, and V. N. Lissotschenko, “Novel continuously shaped diffractive optical elements enable high-efficiency beam shaping,” Proc. SPIE 7640, 764024 (2010).

[Crossref]

A. E. Rosenbluth, S. Bukofsky, C. Fonseca, M. Hibbs, K. Lai, A. Molless, R. N. Singh, and A. K. Wong, “Optimum mask and source patterns to print a given shape,” J. Microlith. Microfab. 1(1), 486 (2002).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

[Crossref]

S. Mosci, L. Rosasco, S. Matteo, A. Verri, and S. Villa, “Solving structured sparsity regularization with proximal methods,” Lect. Notes. Artif. Int. 6322, 418–433 (2010).

[Crossref]

D. Wipf and S. Nagarajan, “A new view of automatic relevance determination,” Advancies in Neural Information Processing Systems 20 (2008).

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[Crossref]

Z. Zhang, T. Jung, S. Makeig, and B. D. Rao, “Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning,” IEEE Trans. Biomed. Eng. 60(2), 300–309 (2013).

[Crossref]

D. P. Wipf and B. D. Rao, “Sparse Bayesian learning for basis selection,” IEEE T. Signal Proces. 52(8), 2153–2164 (2004).

[Crossref]

E. J. Candés, J. Romberg, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52(2), 489–509 (2006).

[Crossref]

S. Mosci, L. Rosasco, S. Matteo, A. Verri, and S. Villa, “Solving structured sparsity regularization with proximal methods,” Lect. Notes. Artif. Int. 6322, 418–433 (2010).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

[Crossref]

A. E. Rosenbluth, S. Bukofsky, C. Fonseca, M. Hibbs, K. Lai, A. Molless, R. N. Singh, and A. K. Wong, “Optimum mask and source patterns to print a given shape,” J. Microlith. Microfab. 1(1), 486 (2002).

[Crossref]

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[Crossref]

A. E. Rosenbluth, S. Bukofsky, C. Fonseca, M. Hibbs, K. Lai, A. Molless, R. N. Singh, and A. K. Wong, “Optimum mask and source patterns to print a given shape,” J. Microlith. Microfab. 1(1), 486 (2002).

[Crossref]

J. T. Carriere, J. Stack, A. D. Kathman, and M. D. Himel, “Advances in DOE modeling and optical performance for SMO applications in immersion lithography at the 32 nm node and beyond,” Proc. SPIE 7640, 764025 (2010).

[Crossref]

K. Huang, S. Tan, Y. Luo, X. Guo, and G. Wang, “Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing,” Pervasive and Mobile Computing 40, 450–463 (2017).

[Crossref]

E. J. Candés, J. Romberg, and T. Tao, “Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information,” IEEE Trans. Inf. Theory 52(2), 489–509 (2006).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

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[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

[Crossref]

A. Erdmann, T. Fühner, T. Schnattinger, and B. Tollkühn, “Towards automatic mask and source optimization for optical lithography,” Proc. SPIE 5377, 646–657 (2004).

[Crossref]

S. Mosci, L. Rosasco, S. Matteo, A. Verri, and S. Villa, “Solving structured sparsity regularization with proximal methods,” Lect. Notes. Artif. Int. 6322, 418–433 (2010).

[Crossref]

S. Mosci, L. Rosasco, S. Matteo, A. Verri, and S. Villa, “Solving structured sparsity regularization with proximal methods,” Lect. Notes. Artif. Int. 6322, 418–433 (2010).

[Crossref]

P. Combettes and V. Wajs, “Signal recovering by proximal forward-backing splitting,” Multiscale Model. Simul. 4(4), 1168–1200 (2005).

[Crossref]

K. Huang, S. Tan, Y. Luo, X. Guo, and G. Wang, “Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing,” Pervasive and Mobile Computing 40, 450–463 (2017).

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J. Wu, F. Liu, L. Jiao, and X. Wang, “Compressive sensing SAR image reconstruction based on Bayesian framework and evolutionary computation,” IEEE T. Image Proces. 20(7), 1904–1911 (2011).

[Crossref]

X. Ma, Z. Wang, Y. Li, G. R. Arce, L. Dong, and J. G. Frias, “Fast optical proximity correction method based on nonlinear compressive sensing,” Opt. Express 26(11), 14479–14498 (2018).

[Crossref]

X. Ma, Z. Wang, H. Lin, Y. Li, G. R. Arce, and L. Zhang, “Optimization of lithography source illumination arrays using diffraction subspaces,” Opt. Express 26(4), 3738–3755 (2018).

[Crossref]

X. Ma, D. Shi, Z. Wang, Y. Li, and G. R. Arce, “Lithographic source optimization based on adaptive projection compressive sensing,” Opt. Express 25(6), 7131–7149 (2017).

[Crossref]

D. Wipf and S. Nagarajan, “A new view of automatic relevance determination,” Advancies in Neural Information Processing Systems 20 (2008).

D. P. Wipf and B. D. Rao, “Sparse Bayesian learning for basis selection,” IEEE T. Signal Proces. 52(8), 2153–2164 (2004).

[Crossref]

A. E. Rosenbluth, S. Bukofsky, C. Fonseca, M. Hibbs, K. Lai, A. Molless, R. N. Singh, and A. K. Wong, “Optimum mask and source patterns to print a given shape,” J. Microlith. Microfab. 1(1), 486 (2002).

[Crossref]

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A. K. Wong, Optical Imaging in Projection Lithography (SPIE, 2005).

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[Crossref]

L. Wang, S. Li, X. Wang, G. Yan, and C. Yang, “Source optimization using particle swarm optimization algorithm in optical lithography,” Acta Opt. Sin. 35(4), 0422002 (2015).

[Crossref]

L. Wang, S. Li, X. Wang, G. Yan, and C. Yang, “Source optimization using particle swarm optimization algorithm in optical lithography,” Acta Opt. Sin. 35(4), 0422002 (2015).

[Crossref]

H. You, Z. Ma, W. Li, and J. Zhu, “A speech enhancement method based on multi-task Bayesian compressive sensing,” IEICE Tran. Inf. & Syst. E100.D(3), 556–563 (2017).

[Crossref]

J. Yu and P. Yu, “Gradient-based fast source mask optimization (SMO),” Proc. SPIE 7973, 797320 (2011).

[Crossref]

Z. Zhang, T. Jung, S. Makeig, and B. D. Rao, “Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning,” IEEE Trans. Biomed. Eng. 60(2), 300–309 (2013).

[Crossref]

X. Gu, P. Zhou, and X. Gu, “Bayesian compressive sensing for thermal imagery using Gaussian-Jeffreys prior,” Infrared Phys. Techn. 83, 51–61 (2017).

[Crossref]

H. You, Z. Ma, W. Li, and J. Zhu, “A speech enhancement method based on multi-task Bayesian compressive sensing,” IEICE Tran. Inf. & Syst. E100.D(3), 556–563 (2017).

[Crossref]

L. Wang, S. Li, X. Wang, G. Yan, and C. Yang, “Source optimization using particle swarm optimization algorithm in optical lithography,” Acta Opt. Sin. 35(4), 0422002 (2015).

[Crossref]

M. E. Tipping, “Spare Bayesian learning and the relevance vector machine,” Appl. Phys. Lett. 1, 211–244 (2000).

[Crossref]

J. Wu, F. Liu, L. Jiao, and X. Wang, “Compressive sensing SAR image reconstruction based on Bayesian framework and evolutionary computation,” IEEE T. Image Proces. 20(7), 1904–1911 (2011).

[Crossref]

D. P. Wipf and B. D. Rao, “Sparse Bayesian learning for basis selection,” IEEE T. Signal Proces. 52(8), 2153–2164 (2004).

[Crossref]

S. Ji, Y. Xue, and L. Carin, “Bayesian compressive sensing,” IEEE T. Signal Proces. 56(6), 2346–2356 (2008).

[Crossref]

Z. Zhang, T. Jung, S. Makeig, and B. D. Rao, “Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning,” IEEE Trans. Biomed. Eng. 60(2), 300–309 (2013).

[Crossref]

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[Crossref]

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H. You, Z. Ma, W. Li, and J. Zhu, “A speech enhancement method based on multi-task Bayesian compressive sensing,” IEICE Tran. Inf. & Syst. E100.D(3), 556–563 (2017).

[Crossref]

X. Gu, P. Zhou, and X. Gu, “Bayesian compressive sensing for thermal imagery using Gaussian-Jeffreys prior,” Infrared Phys. Techn. 83, 51–61 (2017).

[Crossref]

X. Ma, Y. Li, X. Guo, and L. Dong, “Vectorial mask optimization method for robust optical lithography,” J. Micro/Nanolith. MESM. MOEMS. 11(4), 043008 (2012).

[Crossref]

S. G. Hansen, “Source mask polarization optimization,” J. Micro/Nanolithogr., MEMS, MOEMS 10(3), 033003 (2011).

[Crossref]

X. Ma, L. Dong, C. Han, J. Gao, Y. Li, and G. R. Arce, “Gradient-based joint source polarization mask optimization for optical lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 14(2), 023504 (2015).

[Crossref]

X. Guo, Y. Li, L. Dong, L. Liu, X. Ma, and C. Han, “Parametric source-mask-numerical aperture co-optimization for immersion lithography,” J. Micro/Nanolithogr., MEMS, MOEMS 13(4), 043013 (2014).

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[Crossref]

X. Ma, Y. Li, and L. Dong, “Mask optimization approaches in optical lithography based on a vector imaging model,” J. Opt. Soc. Am. A 29(7), 1300–1312 (2012).

[Crossref]

X. Ma, C. Han, Y. Li, L. Dong, and G. R. Arce, “Pixelated source and mask optimization for immersion lithography,” J. Opt. Soc. Am. A 30(1), 112–123 (2013).

[Crossref]

R. Tibshirani, “Regression shrinkage and selection via the Lasso,” J. Roy. Stat. Soc. B. Met. 58(1), 267–288 (1996).

H. Jiang and T. Xing, “A method of source optimization to maximize process window,” Laser Optoelectron. Prog. 52(10), 101101 (2015).

[Crossref]

S. Mosci, L. Rosasco, S. Matteo, A. Verri, and S. Villa, “Solving structured sparsity regularization with proximal methods,” Lect. Notes. Artif. Int. 6322, 418–433 (2010).

[Crossref]

P. Combettes and V. Wajs, “Signal recovering by proximal forward-backing splitting,” Multiscale Model. Simul. 4(4), 1168–1200 (2005).

[Crossref]

D. J. C. MacKay, “Bayesian interpolation,” Neural Comp. 4(3), 415–447 (1992).

[Crossref]

Z. Song, X. Ma, J. Gao, J. Wang, Y. Li, and G. R. Arce, “Inverse lithography source optimization via compressive sensing,” Opt. Express 22(12), 14180–14198 (2014).

[Crossref]

J. Li, Y. Shen, and E. Y. Lam, “Hotspot-aware fast source and mask optimization,” Opt. Express 20(19), 21792–21804 (2012).

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Y. Sun, N. Sheng, T. Li, Y. Li, E. Li, and P. Wei, “Fast nonlinear compressive sensing lithographic source and mask optimization method using Newton-IHTs algorithm,” Opt. Express 27(3), 2754–2770 (2019).

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X. Ma, Z. Wang, H. Lin, Y. Li, G. R. Arce, and L. Zhang, “Optimization of lithography source illumination arrays using diffraction subspaces,” Opt. Express 26(4), 3738–3755 (2018).

[Crossref]

X. Ma, Z. Wang, Y. Li, G. R. Arce, L. Dong, and J. G. Frias, “Fast optical proximity correction method based on nonlinear compressive sensing,” Opt. Express 26(11), 14479–14498 (2018).

[Crossref]

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[Crossref]

X. Ma, D. Shi, Z. Wang, Y. Li, and G. R. Arce, “Lithographic source optimization based on adaptive projection compressive sensing,” Opt. Express 25(6), 7131–7149 (2017).

[Crossref]

X. Ma and G. R. Arce, “Pixel-based simultaneous source and mask optimization for resolution enhancement in optical lithography,” Opt. Express 17(7), 5783–5793 (2009).

[Crossref]

K. Huang, S. Tan, Y. Luo, X. Guo, and G. Wang, “Enhanced radio tomographic imaging with heterogeneous Bayesian compressive sensing,” Pervasive and Mobile Computing 40, 450–463 (2017).

[Crossref]

Y. V. Miklyaev, W. Imgrunt, V. S. Pavelyev, D. G. Kachalov, T. Bizjak, L. Aschke, and V. N. Lissotschenko, “Novel continuously shaped diffractive optical elements enable high-efficiency beam shaping,” Proc. SPIE 7640, 764024 (2010).

[Crossref]

J. T. Carriere, J. Stack, A. D. Kathman, and M. D. Himel, “Advances in DOE modeling and optical performance for SMO applications in immersion lithography at the 32 nm node and beyond,” Proc. SPIE 7640, 764025 (2010).

[Crossref]

A. Erdmann, T. Fühner, T. Schnattinger, and B. Tollkühn, “Towards automatic mask and source optimization for optical lithography,” Proc. SPIE 5377, 646–657 (2004).

[Crossref]

J. Yu and P. Yu, “Gradient-based fast source mask optimization (SMO),” Proc. SPIE 7973, 797320 (2011).

[Crossref]

K. Tian, A. Krasnoperova, D. Melville, A. E. Rosenbluth, D. Gil, J. Tirapu-Azpiroz, K. Lai, S. Bagheri, C. C. Chen, and B. Morgenfeld, “Benefits and trade-offs of global source optimization in optical lithography,” Proc. SPIE 7274, 72740C (2009).

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A. K. Wong, Optical Imaging in Projection Lithography (SPIE, 2005).

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