Based on the theory of information entropy, time series and spatial variation of land use changes of Bijie City in 2009-2013 were analyzed from different dimensions such as land use degree and land use diversity. The ...Based on the theory of information entropy, time series and spatial variation of land use changes of Bijie City in 2009-2013 were analyzed from different dimensions such as land use degree and land use diversity. The result showed that in 2009-2013, the forest vegetation was well protected, and the construction land was under reasonable expansion under the influence of economic development, the land use degree of which developed gradually to width and depth, and the trend of information entropy showed a graduate increase, indicating that land use scale became more reasonable and the area of different land type became more balanced in Bijie in the period. The study results showed that land resources in Bijie City were used rationally under the strategy from central government local government,and Bijie was in the benign development of economic development—resource distribution—scale change. Moreover, Bijie chould further improve land use pattern such as redevelop stock construction land, optimize the industrial land use pattern and mountain agricultural land development in the future.展开更多
This letter investigates an improved blind source separation algorithm based on Maximum Entropy （ME） criteria. The original ME algorithm chooses the fixed exponential or sigmoid ftmction as the nonlinear mapping fun...This letter investigates an improved blind source separation algorithm based on Maximum Entropy （ME） criteria. The original ME algorithm chooses the fixed exponential or sigmoid ftmction as the nonlinear mapping function which can not match the original signal very well. A parameter estimation method is employed in this letter to approach the probability of density function of any signal with parameter-steered generalized exponential function. An improved learning rule and a natural gradient update formula of unmixing matrix are also presented. The algorithm of this letter can separate the mixture of super-Gaussian signals and also the mixture of sub-Gaussian signals. The simulation experiment demonstrates the efficiency of the algorithm.展开更多
基金Supported by the Mutual Fund Project for Soft Science Research of Guizhou Science and Technology Department and Guizhou University of Finance and Economics(Qiankehe LH[2013]7249)~~
文摘Based on the theory of information entropy, time series and spatial variation of land use changes of Bijie City in 2009-2013 were analyzed from different dimensions such as land use degree and land use diversity. The result showed that in 2009-2013, the forest vegetation was well protected, and the construction land was under reasonable expansion under the influence of economic development, the land use degree of which developed gradually to width and depth, and the trend of information entropy showed a graduate increase, indicating that land use scale became more reasonable and the area of different land type became more balanced in Bijie in the period. The study results showed that land resources in Bijie City were used rationally under the strategy from central government local government,and Bijie was in the benign development of economic development—resource distribution—scale change. Moreover, Bijie chould further improve land use pattern such as redevelop stock construction land, optimize the industrial land use pattern and mountain agricultural land development in the future.
文摘This letter investigates an improved blind source separation algorithm based on Maximum Entropy （ME） criteria. The original ME algorithm chooses the fixed exponential or sigmoid ftmction as the nonlinear mapping function which can not match the original signal very well. A parameter estimation method is employed in this letter to approach the probability of density function of any signal with parameter-steered generalized exponential function. An improved learning rule and a natural gradient update formula of unmixing matrix are also presented. The algorithm of this letter can separate the mixture of super-Gaussian signals and also the mixture of sub-Gaussian signals. The simulation experiment demonstrates the efficiency of the algorithm.
