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evolutive Neural Net Fuzzy Filtering: Basic Description

Journal of Intelligent Learning Systems and Applications 2010年第1期2卷 12-18页

作者： Juan C. García Infante J. Jesús Medel Juárez Juan C. Sánchez García 不详

The paper describes the operation principles of the evolutive neuro fuzzy filtering (ENFF) properties, which based on back propagation fuzzy neural net, this filter adaptively choose and emit a decision according with the reference signal changes of an external reference process, in order to actualize the best correct new conditions updating a process. This neural net fuzzy filter mechanism selects the best parameter values into the knowledge base (KB), to update the filter weights giving a good enough answers in accordance with the reference signal in natural sense. The filter architecture includes a decision making stage using an inference into its structure to deduce the filter decisions in accordance with the previous and actual filter answer in order to updates the new decision with respect to the new reference system con-ditions. The filtering process states require that bound into its own time limit as real time system, considering the Ny-quist and Shannon criteria. The characterization of the membership functions builds the knowledge base in probabilis-tic sense with respect to the rules set inference to describe the reference system and deduce the new filter decision, per-forming the ENFF answers. Moreover, the paper describes schematically the neural net architecture and the deci-sion-making stages in order to integrate them into the filter architecture as intelligent system. The results expressed in formal sense use the concepts into the paper references with a simulation of the ENFF into a Kalman filter structure using the Matlab? tool.

关键词： Digital Filters Neuro Fuzzy Systems evolutive Systems Real Time

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The evolutive Law concerning Relationship between Economic Growth and Farmers' Income Increase in Xinjiang since the Reform and Opening-up:An Empirical Analysis of the VEC Model

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Asian Agricultural Research 2013年第1期5卷 4-8页

作者： Xiaojun LIU Junsheng DAI College of Economy and Trade Xinjiang Agricultural University Institute of Agricultural Economy and Information Research Xinjiang Academy of Agricultural Sciences

We select the per capita gross domestic product and rural residents' per capita net income in Xinjiang as the indicator variables to measure economic growth and farmers' income increase in Xinjiang, respectively. We establish the cointegration equation, the vector error correction (VEC) model, and use the impulse response function to conduct empirical analysis of the evolutive law concerning relationship between economic growth and farmers' income increase in Xinjiang during the period 1978-2010. The results show that there is a cointegration relationship between economic growth in Xinjiang and farmers' income increase; the former plays an important role in promoting the latter, following the evolutive law "first intensify, then abate, intensify again, and finally become stable". We put the following policy recommendations: providing preferential policies for farmers, scientifically and rationally guiding the transfer of rural labor; improving the function of agriculture, increasing the proportion of non-farm income; gradually bridging the widening income gap between urban and rural areas, coordinating urban and rural development.

关键词： Economic growth Farmers’ income increase evolutive

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