A time-series similarity measurement method based on wavelet and matrix transform was proposed,and its anti-noise ability,sensitivity and accuracy were discussed. The time-series sequences were compressed into wavelet...A time-series similarity measurement method based on wavelet and matrix transform was proposed,and its anti-noise ability,sensitivity and accuracy were discussed. The time-series sequences were compressed into wavelet subspace,and sample feature vector and orthogonal basics of sample time-series sequences were obtained by K-L transform. Then the inner product transform was carried out to project analyzed time-series sequence into orthogonal basics to gain analyzed feature vectors. The similarity was calculated between sample feature vector and analyzed feature vector by the Euclid distance. Taking fault wave of power electronic devices for example,the experimental results show that the proposed method has low dimension of feature vector,the anti-noise ability of proposed method is 30 times as large as that of plain wavelet method,the sensitivity of proposed method is 1/3 as large as that of plain wavelet method,and the accuracy of proposed method is higher than that of the wavelet singular value decomposition method. The proposed method can be applied in similarity matching and indexing for lager time series databases.展开更多
This paper tries to utilize the methods of stochastic analysis and matrix analysis to research the existential problem of price series. By using the means of time series analysis, the input-output, Markov processes an...This paper tries to utilize the methods of stochastic analysis and matrix analysis to research the existential problem of price series. By using the means of time series analysis, the input-output, Markov processes and the modern matrix analysis, the limiting problem of price balance and vibration in stochastic economic environment has been researched, and surprising conclusions obtained are as following： the probability that the economic collapse time is equal ∞ is 0.展开更多
Mining the inherent persistence property of the time series of wind power is crucial for forecasting and controlling wind power.Few common methods exist that can fully depict and quantify the persistence property.Base...Mining the inherent persistence property of the time series of wind power is crucial for forecasting and controlling wind power.Few common methods exist that can fully depict and quantify the persistence property.Based on the definition of the active power output state of a wind farm,this paper describes the statistical persistence property of the duration time and state transition.Based on the results of our analysis of significant amounts of wind power field measurements,it is found that the duration time of wind power conforms to an inverse Gaussian distribution.Additionally,the state transition matrix of wind power is discovered to yield a ridge property,the gradient of which is related to the time scale of interest.A systemaic methodology is proposed accordingly,allowing the statistical characteristics of the wind power series to be represented appropriately.展开更多
A new(γA,σB)-matrix KP hierarchy with two time series γA and σB,which consists of γA-flow,σB-flow and mixed γA and σB-evolution equations of eigenfunctions,is proposed.The reduction and constrained flows of(...A new(γA,σB)-matrix KP hierarchy with two time series γA and σB,which consists of γA-flow,σB-flow and mixed γA and σB-evolution equations of eigenfunctions,is proposed.The reduction and constrained flows of(γA,σB)matrix KP hierarchy are studied.The dressing method is generalized to the(γA,σB)-matrix KP hierarchy and some solutions are presented.展开更多
基金Projects(60634020, 60904077, 60874069) supported by the National Natural Science Foundation of ChinaProject(JC200903180555A) supported by the Foundation Project of Shenzhen City Science and Technology Plan of China
文摘A time-series similarity measurement method based on wavelet and matrix transform was proposed,and its anti-noise ability,sensitivity and accuracy were discussed. The time-series sequences were compressed into wavelet subspace,and sample feature vector and orthogonal basics of sample time-series sequences were obtained by K-L transform. Then the inner product transform was carried out to project analyzed time-series sequence into orthogonal basics to gain analyzed feature vectors. The similarity was calculated between sample feature vector and analyzed feature vector by the Euclid distance. Taking fault wave of power electronic devices for example,the experimental results show that the proposed method has low dimension of feature vector,the anti-noise ability of proposed method is 30 times as large as that of plain wavelet method,the sensitivity of proposed method is 1/3 as large as that of plain wavelet method,and the accuracy of proposed method is higher than that of the wavelet singular value decomposition method. The proposed method can be applied in similarity matching and indexing for lager time series databases.
文摘This paper tries to utilize the methods of stochastic analysis and matrix analysis to research the existential problem of price series. By using the means of time series analysis, the input-output, Markov processes and the modern matrix analysis, the limiting problem of price balance and vibration in stochastic economic environment has been researched, and surprising conclusions obtained are as following： the probability that the economic collapse time is equal ∞ is 0.
基金supported by the Natural High Technology Research and Development of China(863 Program)(Grant No.2011AA05A112)the National Natural Science Foundation of China(Grant No.51377027)ABB(China)Ltd.
文摘Mining the inherent persistence property of the time series of wind power is crucial for forecasting and controlling wind power.Few common methods exist that can fully depict and quantify the persistence property.Based on the definition of the active power output state of a wind farm,this paper describes the statistical persistence property of the duration time and state transition.Based on the results of our analysis of significant amounts of wind power field measurements,it is found that the duration time of wind power conforms to an inverse Gaussian distribution.Additionally,the state transition matrix of wind power is discovered to yield a ridge property,the gradient of which is related to the time scale of interest.A systemaic methodology is proposed accordingly,allowing the statistical characteristics of the wind power series to be represented appropriately.
基金Supported by the National Science Foundation of China under Grant Nos. 10801083,10901090,11171175China Postdoctoral Science Funded Project (20110490408)Chinese Universities Scientific Fund under Grant No. 2011JS041
文摘A new(γA,σB)-matrix KP hierarchy with two time series γA and σB,which consists of γA-flow,σB-flow and mixed γA and σB-evolution equations of eigenfunctions,is proposed.The reduction and constrained flows of(γA,σB)matrix KP hierarchy are studied.The dressing method is generalized to the(γA,σB)-matrix KP hierarchy and some solutions are presented.
