A Fuzzy-Matching Model With Grid Reduction for Lithography Hotspot Detection
暂无分享,去创建一个
Wan-Yu Wen | Shih-Chieh Chang | Sheng-Yuan Lin | Jing-Yi Chen | Jin-Cheng Li | Shih-Chieh Chang | Sheng-Yuan Lin | Jing-Yi Chen | Jin-Cheng Li | Wan-Yu Wen
[1] Frank Liu,et al. Predicting variability in nanoscale lithography processes , 2009, 2009 46th ACM/IEEE Design Automation Conference.
[2] Malgorzata Marek-Sadowska,et al. Efficient approach to early detection of lithographic hotspots using machine learning systems and pattern matching , 2011, Advanced Lithography.
[3] Philippe Hurat,et al. Layout printability optimization using a silicon simulation methodology , 2004, International Symposium on Signals, Circuits and Systems. Proceedings, SCS 2003. (Cat. No.03EX720).
[4] David Z. Pan,et al. Machine learning based lithographic hotspot detection with critical-feature extraction and classification , 2009, 2009 IEEE International Conference on IC Design and Technology.
[5] David Z. Pan,et al. EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation , 2012, 17th Asia and South Pacific Design Automation Conference.
[6] Costas J. Spanos,et al. Clustering and pattern matching for an automatic hotspot classification and detection system , 2009, Advanced Lithography.
[7] Iris Hui-Ru Jiang,et al. Machine-Learning-Based Hotspot Detection Using Topological Classification and Critical Feature Extraction , 2015, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..
[8] Jie Yang,et al. DRC Plus: augmenting standard DRC with pattern matching on 2D geometries , 2007, SPIE Advanced Lithography.
[9] Iris Hui-Ru Jiang,et al. Machine-learning-based hotspot detection using topological classification and critical feature extraction , 2013, 2013 50th ACM/EDAC/IEEE Design Automation Conference (DAC).
[10] Charles C. Chiang,et al. Accurate detection for process-hotspots with vias and incomplete specification , 2007, ICCAD 2007.
[11] J. Andres Torres,et al. Multi-selection method for physical design verification applications , 2011, Advanced Lithography.
[12] Yici Cai,et al. Efficient range pattern matching algorithm for process-hotspot detection , 2008, IET Circuits Devices Syst..
[13] Ieee Circuits,et al. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems information for authors , 2018, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.
[14] Wan-Yu Wen,et al. A novel fuzzy matching model for lithography hotspot detection , 2013, 2013 50th ACM/EDAC/IEEE Design Automation Conference (DAC).
[15] Jingyu Xu,et al. Accurate detection for process-hotspots with vias and incomplete specification , 2007, 2007 IEEE/ACM International Conference on Computer-Aided Design.
[16] J. Andres Torres,et al. ICCAD-2012 CAD contest in fuzzy pattern matching for physical verification and benchmark suite , 2012, 2012 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).
[17] Malgorzata Marek-Sadowska,et al. Detecting context sensitive hot spots in standard cell libraries , 2009, Advanced Lithography.
[18] Juhwan Kim,et al. Hotspot detection on post-OPC layout using full-chip simulation-based verification tool: a case study with aerial image simulation , 2003, SPIE Photomask Technology.
[19] Andrew B. Kahng,et al. Fast dual graph-based hotspot detection , 2006, SPIE Photomask Technology.
[20] David Z. Pan,et al. Accurate lithography hotspot detection based on PCA-SVM classifier with hierarchical data clustering , 2014, Advanced Lithography.
[21] Fedor G. Pikus,et al. High performance lithographic hotspot detection using hierarchically refined machine learning , 2011, 16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011).
[22] Heng Tao Shen,et al. Principal Component Analysis , 2009, Encyclopedia of Biometrics.
[23] Kazuhiko Takahashi,et al. Study of hot spot detection using neural networks judgment , 2007, Photomask Japan.
[24] Malgorzata Marek-Sadowska,et al. Rapid layout pattern classification , 2011, 16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011).