Based on Lucovsky equation,the response solution of 1-D position sensitive detector(PSD) is given under the condition of parallel light oblique incidence and Gaussian beam oblique incidence,and the response characteri...Based on Lucovsky equation,the response solution of 1-D position sensitive detector(PSD) is given under the condition of parallel light oblique incidence and Gaussian beam oblique incidence,and the response characteristics are analyzed by numerical calculation. The relation between oblique incident angle and output current is introduced and illustrated.展开更多
There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling ...There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery.展开更多
Recently, many programs have been developed for simulation or analysis of the different parameters of light propagation in optical fibers, either for sensing or for communication purposes. In this paper, it is shown t...Recently, many programs have been developed for simulation or analysis of the different parameters of light propagation in optical fibers, either for sensing or for communication purposes. In this paper, it is shown the COMSOL Multiphysics as a fairly robust and simple program, due to the existence of a graphical environment, to perform simulations with good accuracy. Results are compared with other simulation analysis, focusing on the surface plasmon resonance （SPR） phenomena for refractive index sensing in a D-type optical fiber, where the characteristics of the material layers, in terms of the type and thickness, and the residual fiber cladding thickness are optimized.展开更多
基金Program of the Science and Technology Department of Fujian Province(2007F5040)
文摘Based on Lucovsky equation,the response solution of 1-D position sensitive detector(PSD) is given under the condition of parallel light oblique incidence and Gaussian beam oblique incidence,and the response characteristics are analyzed by numerical calculation. The relation between oblique incident angle and output current is introduced and illustrated.
基金supported by the National Natural Science Foundation of China(Grant Nos.41272359&11001019)the Specialized Research Fund for the Doctoral Program of Higher Education(SRFDP)the Fundamental Research Funds for the Central Universities
文摘There is a certain degree of ambiguity associated with remote sensing as a means of performing earth observations.Using interval-valued data to describe clustering prototype features may be more suitable for handling the fuzzy nature of remote sensing data,which is caused by the uncertainty and heterogeneity in the surface spectral reflectance of ground objects.After constructing a multi-spectral interval-valued model of source data and defining a distance measure to achieve the maximum dissimilarity between intervals,an interval-valued fuzzy c-means(FCM)clustering algorithm that considers both the functional characteristics of fuzzy clustering algorithms and the interregional features of ground object spectral reflectance was applied in this study.Such a process can significantly improve the clustering effect;specifically,the process can reduce the synonym spectrum phenomenon and the misclassification caused by the overlap of spectral features between classes of clustering results.Clustering analysis experiments aimed at land cover classification using remote sensing imagery from the SPOT-5 satellite sensor for the Pearl River Delta region,China,and the TM sensor for Yushu,Qinghai,China,were conducted,as well as experiments involving the conventional FCM algorithm,the results of which were used for comparative analysis.Next,a supervised classification method was used to validate the clustering results.The final results indicate that the proposed interval-valued FCM clustering is more effective than the conventional FCM clustering method for land cover classification using multi-spectral remote sensing imagery.
文摘Recently, many programs have been developed for simulation or analysis of the different parameters of light propagation in optical fibers, either for sensing or for communication purposes. In this paper, it is shown the COMSOL Multiphysics as a fairly robust and simple program, due to the existence of a graphical environment, to perform simulations with good accuracy. Results are compared with other simulation analysis, focusing on the surface plasmon resonance （SPR） phenomena for refractive index sensing in a D-type optical fiber, where the characteristics of the material layers, in terms of the type and thickness, and the residual fiber cladding thickness are optimized.
