Identification algorithm for a kind of fractional order system

The state-space representation of linear time-invariant (LTI) fractional order systems is introduced, and a proof of their stability theory is also given. Then an efficient identification algorithm is proposed for those fractional order systems. The basic idea of the algorithm is to compute fractional derivatives and the filter simultaneously, i.e., the filtered fractional derivatives can be obtained by computing them in one step, and then system identification can be fulfilled by the least square method. The instrumental variable method is also used in the identification of fractional order systems. In this way, even if there is colored noise in the systems, the unbiased estimation of the parameters can still be obtained. Finally an example of identifying a viscoelastic system is given to show the effectiveness of the aforementioned method.

Iterative identification of discrete-time output-error model with time delay

The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function model parameters and time delay are alternately fixed to estimate each other.The instrumental variable technique is applied to guarantee consistent estimation against measurement noise.A noteworthy merit of the proposed method is that it can handle fractional time delay estimation,compared to existing methods commonly assuming that the time delay is an integer multiple of the sampling interval.The identifiability analysis for time delay is addressed and correspondingly,some guidelines are provided for practical implementation of the proposed method.Numerical and experimental examples are presented to illustrate the effectiveness of the proposed method.

Intergenerational Transmission of Income Gap for Chinese Urban and Rural Households

An accurate understanding of the intergenerational transmission of income gap is the foundation for theoretical research and policy formulation to address this issue. This paper has employed the method of two sample instrumental variables to effectively integrate CHIP data and CFPS data and correct the temporal income bias, life-cycle bias and coresidence bias, which are common problems in existing studies, and investigated the tendencies of intergenerational transmission of income gap for China's urban and rural households between 2002 and 2012. Results of empirical study indicate that the intergenerational transmission of income gap for China's urban and rural households has been on the decline yet the level of intergenerational transmission is greater for urban residents than for rural residents. This level of intergenerational transmission of income gap in China is at a medium international level lower than that of countries like the United States, Brazil and Japan and higher than that of Sweden and Chinese Taiwan. Further analysis of the intergenerational mobility of various income groups suggests the following: the intergenerational solidification of the bottom and top income groups of urban residents has significantly improved, which is the source for the reduction of intergenerational transmission of income gap. Rural residents of bottom income group are vulnerable to falling into the trap of intergenerational transmission of low income. In order to mitigate the intergenerational transmission of income gap, efforts must be made to improve educational allowance policy and increase the opportunities for children from poor and underprivileged families to receive education and to eliminate the divide of labor markets to create equal job opportunities for each and every worker.

The effects of population aging on industrial structure upgrading:Empirical analysis of provincial and threshold characteristics in China

Global population aging trends are intensifying,presenting multifaceted economic and social challenges for countries worldwide.As the world’s largest developing country,China has entered a phase of extreme demographic aging,posing significant questions about its impact on the ongoing upgrading of industrial structures.How does this demographic shift influence the upgrading of industrial structures,and does technological innovation mitigate or exacerbate this impact?The empirical results indicate that population aging impedes upgrading the industrial structure,while technological innovation positively affects the relationship between the two.Moreover,using technological innovation as a threshold variable,the impact of population aging on industrial structure upgrading evolves in a“gradient”manner from“impediment”to“insignificant”to“promotion”as the technological innovation levels increase.These findings offer practical guidance for tailoring industrial policies to different stages of technological advancement.