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According to the usual approximation scheme, we present a more biologically plausible so-called second order spiking perceptron with renewal process inputs, which employs both first and second statistics, i.e. the means, variances and correlations of the synaptic input. We show that such perceptron, even a single neuron, is able to perform complex non-linear tasks like the XOR problem, which is impossible...
The paper mainly studies the designs of LA, LS and LAS codes. Then it makes simulation for theirs auto-correlation functions and cross-correlation functions. Simulation and analysis show that, LAS code has zero cross-correlation in the "zero interference window", and has only an impulse auto-correlation in the "zero interference window", and these excellent features help to eliminate...
The present study shows that the debt-to-asset ratio of China's state-owned enterprises and of China's industrial enterprises basically hold constant in recent years after reaching a peak in 1995. The correlation between the debt ratio of China's state-owned enterprises and GDP growth rate is small, yet the correlation between the debt ratio of China's state-owned enterprises and inflation rate is...
Fully utilizing the structural data and nonstructural data in the age of informationization and obtaining the efficient information using data mining technique to direct the decision making in regional management have become more important in China. Discriminant analysis is a typical data mining method. In the view of knowledge management in different regions, discriminant analysis based on DEA model...
In highly volatile market conditions it's always difficult to predict returns using heteroscedastic Garch models. This paper tries to investigate the impact of sample data inputs over forecast using nested conditional mean ARMAX(2, 2, 0) and conditional variance Garch(1, 1), Gjr-garch(1, 1) and Egarch(1, 1) models. Research also tries to indentify relationship between outcome of formal hypothesis...
The paper advances a method of predicting, based on their market share and turnover, which companies in a given market would be subject to hard-core agreements between competitors, which break the provisions of the competition law. We track the correlations between the market share, turnover and anticompetitive behaviors, and we construct a neural network model to discriminate between companies not...
The telecommunications policy and industry development in China have attracted sizable interests. However, there is a lack of empirical studies to evaluate the effect of China's telecommunications reform and restructure. In line with most scholars opinions, we believe that telecommunications restructure in China began in 1994 and has become ldquovery dramatic and far-reachingrdquo since 1998. We treat...
There is a wealth of information collected about national level socio-economic indicators across all countries each year. These indicators are important in recognizing the level of development in certain aspects of a particular country, and are also essential in international policy making. However with past data spanning several decades and many hundreds of indicators evaluated, trying to get an...
A approach is suggested for designing and developing a trade surplus influence factors correlation analysis application where GMDH principle is used for generating it more easily. This approach uses self-organizing data mining importing the concept of evolution based on principle of GMDH and enables the knowledge extraction process on a highly automated level and generates optimal complex model in...
According to the usual approximation scheme, we extend the spike-rate perceptron to develop a more biologically plausible so-called extended spike-rate perceptron with renewal process inputs, which employs both first and second statistics, i.e. the means, variances and correlations of the synaptic input. We show that such perceptron, even a single neuron, is able to perform complex non-linear tasks...
The fundamental secret-key rate vs. privacy-leakage rate trade-offs for secret-key generation and transmission for i.i.d. Gaussian biometric sources are determined. These results are the Gaussian equivalents of the results that were obtained for the discrete case by the authors and independently by Lai et al. in 2008. Also the effect that binary quantization of the biometric sequences has on the ratio...
Most of the biclustering algorithms for the analysis of high dimensional gene expression data use some distance measure or correlation coefficient between a pair of genes as the similarity measure. These measures capture only linear relationships between the genes but non linear relationships may exist amongst them. Mutual information is a more general measure to investigate relationships (positive,...
Copulas are functions that join or couple multivariate distribution functions to their one dimensional marginal distribution functions. Alternatively, copulas are multivariate distribution functions whose one-dimensional margins are uniform on the interval (0,1). The appeal of copula function lies in the fact that it eliminates the implied reliance on the multivariate normal or the assumption that...
In general, credit-scoring models suffer from a sample-selection bias. This paper uses the bivariate probit approach to estimate an unbiased models scoring model. The data set with large commercial loans data provided by a commercial bank of China to estimate the model contains some financial and firm information on both rejected and approved applicants. In the bivariate probit model, we find a significant...
Taking the estimation of area-percent about different land use in certain city as an example, we evaluated the effect of simple random sampling, stratified sampling based on administrator region, stratified sampling based on knowledge and stratified-systematic sampling based on spatial autocorrelation. Sample size and precision (standard deviation) were made decision criteria to estimate the effect...
Traditional discriminative classification method makes little attempt to reveal the probabilistic structure and the correlation within both input and output spaces. In the scenario of multi-label classification, most of the classifiers simply assume the predefined classes are independently distributed, which would definitely hinder the classification performance when there are intrinsic correlations...
Current information networks acting as the fundamental infrastructure of our society, possess the economic-social characteristics, so, in formulating new definitions and computational models for the networked environment, it is imperative to take economic and incentive considerations into account. The paperpsilas contribution is twofold: first, to characterize the economic implication of some proposed...
For the problem of soil moisture prediction, existing approaches in literature [M. Kashif et al., 2006; Y. Shao et al., 1997] usually utilize as many decision factors as possible, e.g. rainfall, solar irradiance, drainage, etc. However, the redundancy aspect of the decision factors has not been studied rigorously. Previous research work in data mining has shown that removing redundant features improves...
Grey relational analysis is an important part of the grey systems theory, and it is the basis of the grey clustering analysis, grey decision-making and grey controlling. In this paper, we provided the definitions of parallel, uniform and order-keeping properties. We constructed a new grey relational model. By theoretical proving we knew that the model is not only satisfied to the normality, whole...
The essence of traditional incidence model is incidence analysis based on the certain real, which can not handle incidence analysis among uncertain number sequences. This article gives a calculation model of grey absolute incidence degree between uncertainty sequence data based on interval grey number expression. The model can analyze the incidence degree of two interval grey sequences groups which...
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