A test of deep seismic reflection profiling across the central uplift or metamorphic belt of the Qiangtang （羌塘） terrane, Tibet plateau, provides a first image of the crustal structure. Complex reflection patterns ...A test of deep seismic reflection profiling across the central uplift or metamorphic belt of the Qiangtang （羌塘） terrane, Tibet plateau, provides a first image of the crustal structure. Complex reflection patterns in the upper crust are interpreted as a series of folds and thrusts, and bivergent reflections in the lower crust may represent a convergence between the Indian and the Eurasian plates.展开更多
A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in tr...A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in traditional identification methods.Firstly,a neuro-fuzzy based Hammerstein model is constructed to describe the nonlinearity of Hammerstein process without any prior process knowledge.Secondly,a kind of special test signal is used to separate the link parts of the Hammerstein model.More specifically,the conception of PDF is introduced to solve the identification problem of the neuro-fuzzy Hammerstein model.The antecedent parameters are estimated by a clustering algorithm,while the consequent parameters of the model are identified by designing a virtual PDF control system in which the PDF of the modeling error is estimated and controlled to converge to the target.The proposed method not only guarantees the accuracy of the model but also dominates the spatial distribution of PDF of the model error to improve the generalization ability of the model.Simulated results show the effectiveness of the proposed method.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 40830316, 40874045 and 40704016)the Ministry of Science and Technology of China (Nos. SinoProbe-02, 2006DFA21340)+1 种基金the Ministry of Land and Resources of China (Nos. 2004-06, 200811021)the Open Fund of Key Laboratory of Geo-detection of China Uni-versity of Geosciences (Beijing) (No. GDL0603)
文摘A test of deep seismic reflection profiling across the central uplift or metamorphic belt of the Qiangtang （羌塘） terrane, Tibet plateau, provides a first image of the crustal structure. Complex reflection patterns in the upper crust are interpreted as a series of folds and thrusts, and bivergent reflections in the lower crust may represent a convergence between the Indian and the Eurasian plates.
基金National Natural Science Foundation of China(No.61374044)Shanghai Municipal Science and Technology Commission,China(No.15510722100)+2 种基金Shanghai Municipal Education Commission,China(No.14ZZ088)Shanghai Talent Development Plan,ChinaShanghai Baoshan Science and Technology Commission,China(No.bkw2013120)
文摘A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in traditional identification methods.Firstly,a neuro-fuzzy based Hammerstein model is constructed to describe the nonlinearity of Hammerstein process without any prior process knowledge.Secondly,a kind of special test signal is used to separate the link parts of the Hammerstein model.More specifically,the conception of PDF is introduced to solve the identification problem of the neuro-fuzzy Hammerstein model.The antecedent parameters are estimated by a clustering algorithm,while the consequent parameters of the model are identified by designing a virtual PDF control system in which the PDF of the modeling error is estimated and controlled to converge to the target.The proposed method not only guarantees the accuracy of the model but also dominates the spatial distribution of PDF of the model error to improve the generalization ability of the model.Simulated results show the effectiveness of the proposed method.
