This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative(MIGI) approach is proposed to optimize the distance me...This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative(MIGI) approach is proposed to optimize the distance metric of locally weighted learning(LWL), and a novel non-parametric modeling technique is developed for a nonlinear ship maneuvering system. This proposed method’s advantages are as follows: first, it can avoid the unmodeled dynamics and multicollinearity inherent to the conventional parametric model; second, it eliminates the over-learning or underlearning and obtains the optimal distance metric; and third, the MIGI is not sensitive to the initial parameter value and requires less time during the training phase. These advantages result in a highly accurate mathematical modeling technique that can be conveniently implemented in applications. To verify the characteristics of this mathematical model, two examples are used as the model platforms to study the ship maneuvering.展开更多
Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to rea...Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to realize the identification and separation of the Hammerstein model.As a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable parameters.The auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein model.The auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation length.The simulation results show the efficiency of the proposed method.展开更多
Aimed at the problems of small gradient, low learning rate, slow convergence error when the DBN using back-propagation process to fix the network connection weight and bias, proposing a new algorithm that combines wit...Aimed at the problems of small gradient, low learning rate, slow convergence error when the DBN using back-propagation process to fix the network connection weight and bias, proposing a new algorithm that combines with multi-innovation theory to improve standard DBN algorithm, that is the multi-innovation DBN(MI-DBN). It sets up a new model of back-propagation process in DBN algorithm, making the use of single innovation in previous algorithm extend to the use of innovation of the preceding multiple period, thus increasing convergence rate of error largely. To study the application of the algorithm in the social computing, and recognize the meaningful information about the handwritten numbers in social networking images. This paper compares MI-DBN algorithm with other representative classifiers through experiments. The result shows that MI-DBN algorithm, comparing with other representative classifiers, has a faster convergence rate and a smaller error for MNIST dataset recognition. And handwritten numbers on the image also have a precise degree of recognition.展开更多
The urban grass-roots library is an important part of the public cultural service system,and also a place to carry out national reading and lifelong learning,which is of great significance to the construction of a lea...The urban grass-roots library is an important part of the public cultural service system,and also a place to carry out national reading and lifelong learning,which is of great significance to the construction of a learning society.In this paper,the development and evolution of urban grassroots libraries in China are reviewed,and the current situation and usage issues of grassroots libraries in Beijing are analyzed.Moreover,the development strategy of idea stores in London,UK is studied,and characteristics are summarized,and possible references are sought.In the new era,urban grassroots libraries should integrate into communities with multiple functions and play a more sufficient role in public education,learning and training,and other aspects.展开更多
We first look at the possibility that the ideas of event horizons for black holes may have their application only in early universe conditions whereas Corda’s ground breaking work rejecting event horizons may be due ...We first look at the possibility that the ideas of event horizons for black holes may have their application only in early universe conditions whereas Corda’s ground breaking work rejecting event horizons may be due to the formation of quantum mechanics free of an embedding in 5 dimensions allowing for a simpler more direct approach, which rejects the idea of a firewall. First, we present the idea of classical black hole physics applied only once as for the early universe, whereas in such a setting, there may be a way to present NLED and structure formation due to an initial entropy approach as outlined. Then the ideas of Corda’s breakthrough are presented for the reasons he illuminated in his recent work, due to QM being fully formed separate from higher dimensional embedding after the initial evolution of the universe.展开更多
基金financially supported in part by the National High Technology Research and Development Program of China(863Program,Grant No.2015AA016404)the National Natural Science Foundation of China(Grant Nos.51109020,51179019 and 51779029)the Fundamental Research Program for Key Laboratory of the Education Department of Liaoning Province(Grant No.LZ2015006)
文摘This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative(MIGI) approach is proposed to optimize the distance metric of locally weighted learning(LWL), and a novel non-parametric modeling technique is developed for a nonlinear ship maneuvering system. This proposed method’s advantages are as follows: first, it can avoid the unmodeled dynamics and multicollinearity inherent to the conventional parametric model; second, it eliminates the over-learning or underlearning and obtains the optimal distance metric; and third, the MIGI is not sensitive to the initial parameter value and requires less time during the training phase. These advantages result in a highly accurate mathematical modeling technique that can be conveniently implemented in applications. To verify the characteristics of this mathematical model, two examples are used as the model platforms to study the ship maneuvering.
基金National Natural Science Foundation of China(No.61374044)Shanghai Science Technology Commission,China(Nos.15510722100,16111106300)
文摘Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to realize the identification and separation of the Hammerstein model.As a result,the identification of the dynamic linear part can be separated from the static nonlinear elements without any redundant adjustable parameters.The auxiliary model based multi-innovation stochastic gradient algorithm was applied to identifying the serial link parameters of the Hammerstein model.The auxiliary model based multi-innovation stochastic gradient algorithm can avoid the influence of noise and improve the identification accuracy by changing the innovation length.The simulation results show the efficiency of the proposed method.
文摘Aimed at the problems of small gradient, low learning rate, slow convergence error when the DBN using back-propagation process to fix the network connection weight and bias, proposing a new algorithm that combines with multi-innovation theory to improve standard DBN algorithm, that is the multi-innovation DBN(MI-DBN). It sets up a new model of back-propagation process in DBN algorithm, making the use of single innovation in previous algorithm extend to the use of innovation of the preceding multiple period, thus increasing convergence rate of error largely. To study the application of the algorithm in the social computing, and recognize the meaningful information about the handwritten numbers in social networking images. This paper compares MI-DBN algorithm with other representative classifiers through experiments. The result shows that MI-DBN algorithm, comparing with other representative classifiers, has a faster convergence rate and a smaller error for MNIST dataset recognition. And handwritten numbers on the image also have a precise degree of recognition.
基金the National Natural Science Foundation of China(51708001).
文摘The urban grass-roots library is an important part of the public cultural service system,and also a place to carry out national reading and lifelong learning,which is of great significance to the construction of a learning society.In this paper,the development and evolution of urban grassroots libraries in China are reviewed,and the current situation and usage issues of grassroots libraries in Beijing are analyzed.Moreover,the development strategy of idea stores in London,UK is studied,and characteristics are summarized,and possible references are sought.In the new era,urban grassroots libraries should integrate into communities with multiple functions and play a more sufficient role in public education,learning and training,and other aspects.
文摘We first look at the possibility that the ideas of event horizons for black holes may have their application only in early universe conditions whereas Corda’s ground breaking work rejecting event horizons may be due to the formation of quantum mechanics free of an embedding in 5 dimensions allowing for a simpler more direct approach, which rejects the idea of a firewall. First, we present the idea of classical black hole physics applied only once as for the early universe, whereas in such a setting, there may be a way to present NLED and structure formation due to an initial entropy approach as outlined. Then the ideas of Corda’s breakthrough are presented for the reasons he illuminated in his recent work, due to QM being fully formed separate from higher dimensional embedding after the initial evolution of the universe.