The endochronic equations proposed by Valanis (1980) were extended to a finite deformation range. Jaumanns rate, Fus rate and Wus rate were incorporated into the endochronic equations to analyze simple shear finite de...The endochronic equations proposed by Valanis (1980) were extended to a finite deformation range. Jaumanns rate, Fus rate and Wus rate were incorporated into the endochronic equations to analyze simple shear finite deformation. Incremental equations and numerical solutions are deduced for three endochronic objective models. The results show that an oscillatory shear stress response to a monotonically increasing shear strain occurs when the Jaumanns rate objective model is employed for endochronic materials. The oscillatory response is dependent on the adopted objective rate. Compared with the Jaumanns rate, the Fus rate and the Wus rate satisfy the restrictions to elastic-plastic constitutive relations and are in agreement with the experimental results.展开更多
Designing detection algorithms with high efficiency for Synthetic Aperture Radar(SAR) imagery is essential for the operator SAR Automatic Target Recognition(ATR) system.This work abandons the detection strategy of vis...Designing detection algorithms with high efficiency for Synthetic Aperture Radar(SAR) imagery is essential for the operator SAR Automatic Target Recognition(ATR) system.This work abandons the detection strategy of visiting every pixel in SAR imagery as done in many traditional detection algorithms,and introduces the gridding and fusion idea of different texture fea-tures to realize fast target detection.It first grids the original SAR imagery,yielding a set of grids to be classified into clutter grids and target grids,and then calculates the texture features in each grid.By fusing the calculation results,the target grids containing potential maneuvering targets are determined.The dual threshold segmentation technique is imposed on target grids to obtain the regions of interest.The fused texture features,including local statistics features and Gray-Level Co-occurrence Matrix(GLCM),are investigated.The efficiency and superiority of our proposed algorithm were tested and verified by comparing with existing fast de-tection algorithms using real SAR data.The results obtained from the experiments indicate the promising practical application val-ue of our study.展开更多
文摘The endochronic equations proposed by Valanis (1980) were extended to a finite deformation range. Jaumanns rate, Fus rate and Wus rate were incorporated into the endochronic equations to analyze simple shear finite deformation. Incremental equations and numerical solutions are deduced for three endochronic objective models. The results show that an oscillatory shear stress response to a monotonically increasing shear strain occurs when the Jaumanns rate objective model is employed for endochronic materials. The oscillatory response is dependent on the adopted objective rate. Compared with the Jaumanns rate, the Fus rate and the Wus rate satisfy the restrictions to elastic-plastic constitutive relations and are in agreement with the experimental results.
基金Supported by the National Natural Science Foundation of China (No. 61032001, No.61002045)
文摘Designing detection algorithms with high efficiency for Synthetic Aperture Radar(SAR) imagery is essential for the operator SAR Automatic Target Recognition(ATR) system.This work abandons the detection strategy of visiting every pixel in SAR imagery as done in many traditional detection algorithms,and introduces the gridding and fusion idea of different texture fea-tures to realize fast target detection.It first grids the original SAR imagery,yielding a set of grids to be classified into clutter grids and target grids,and then calculates the texture features in each grid.By fusing the calculation results,the target grids containing potential maneuvering targets are determined.The dual threshold segmentation technique is imposed on target grids to obtain the regions of interest.The fused texture features,including local statistics features and Gray-Level Co-occurrence Matrix(GLCM),are investigated.The efficiency and superiority of our proposed algorithm were tested and verified by comparing with existing fast de-tection algorithms using real SAR data.The results obtained from the experiments indicate the promising practical application val-ue of our study.
