Optical proximity correction (OPC) systems require an accurate and fast way to predict how patterns will be transferred to the wafer.Based on Gabor's 'reduction to principal waves',a partially coherent ima...Optical proximity correction (OPC) systems require an accurate and fast way to predict how patterns will be transferred to the wafer.Based on Gabor's 'reduction to principal waves',a partially coherent imaging system can be represented as a superposition of coherent imaging systems,so an accurate and fast sparse aerial image intensity calculation algorithm for lithography simulation is presented based on convolution kernels,which also include simulating the lateral diffusion and some mask processing effects via Gaussian filter.The simplicity of this model leads to substantial computational and analytical benefits.Efficiency of this method is also shown through simulation results.展开更多
Zipf＇s approach in linguistics is utilized to analyze the statistical features of frequency and correlation of 16 nearest neighboring nucleotides （AA, AC, AG, …, TT） in 12 human chro- mosomes （Y, 22, 21, 20, 19, ...Zipf＇s approach in linguistics is utilized to analyze the statistical features of frequency and correlation of 16 nearest neighboring nucleotides （AA, AC, AG, …, TT） in 12 human chro- mosomes （Y, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, and 12）. It is found that these statistical features of nearest neighboring nucleotides in human genome： （i） the frequency distribution is a linear function, and （ii） the correlation distribution is an inverse function. The coefficients of the linear function and inverse function depend on the GC content. It proposes the correlation distribution of nearest neighboring nucleotides for the first time and extends the descriptor about nearest neighboring nueleotides.展开更多
The Neighborhood Preserving Embedding(NPE) algorithm is recently proposed as a new dimensionality reduction method.However, it is confined to linear transforms in the data space.For this, based on the NPE algorithm, a...The Neighborhood Preserving Embedding(NPE) algorithm is recently proposed as a new dimensionality reduction method.However, it is confined to linear transforms in the data space.For this, based on the NPE algorithm, a new nonlinear dimensionality reduction method is proposed, which can preserve the local structures of the data in the feature space.First, combined with the Mercer kernel, the solution to the weight matrix in the feature space is gotten and then the corresponding eigenvalue problem of the Kernel NPE(KNPE) method is deduced.Finally, the KNPE algorithm is resolved through a transformed optimization problem and QR decomposition.The experimental results on three real-world data sets show that the new method is better than NPE, Kernel PCA(KPCA) and Kernel LDA(KLDA) in performance.展开更多
文摘Optical proximity correction (OPC) systems require an accurate and fast way to predict how patterns will be transferred to the wafer.Based on Gabor's 'reduction to principal waves',a partially coherent imaging system can be represented as a superposition of coherent imaging systems,so an accurate and fast sparse aerial image intensity calculation algorithm for lithography simulation is presented based on convolution kernels,which also include simulating the lateral diffusion and some mask processing effects via Gaussian filter.The simplicity of this model leads to substantial computational and analytical benefits.Efficiency of this method is also shown through simulation results.
基金ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China （No.20173023 and No.90203012） and the Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘Zipf＇s approach in linguistics is utilized to analyze the statistical features of frequency and correlation of 16 nearest neighboring nucleotides （AA, AC, AG, …, TT） in 12 human chro- mosomes （Y, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, and 12）. It is found that these statistical features of nearest neighboring nucleotides in human genome： （i） the frequency distribution is a linear function, and （ii） the correlation distribution is an inverse function. The coefficients of the linear function and inverse function depend on the GC content. It proposes the correlation distribution of nearest neighboring nucleotides for the first time and extends the descriptor about nearest neighboring nueleotides.
文摘The Neighborhood Preserving Embedding(NPE) algorithm is recently proposed as a new dimensionality reduction method.However, it is confined to linear transforms in the data space.For this, based on the NPE algorithm, a new nonlinear dimensionality reduction method is proposed, which can preserve the local structures of the data in the feature space.First, combined with the Mercer kernel, the solution to the weight matrix in the feature space is gotten and then the corresponding eigenvalue problem of the Kernel NPE(KNPE) method is deduced.Finally, the KNPE algorithm is resolved through a transformed optimization problem and QR decomposition.The experimental results on three real-world data sets show that the new method is better than NPE, Kernel PCA(KPCA) and Kernel LDA(KLDA) in performance.
