The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors,however the characteristics of the signal need to be extrac...The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors,however the characteristics of the signal need to be extracted accurately.Although the existing EMD(empirical mode decomposition)and EEMD(ensemble empirical mode decomposition)are suitable for processing non-stationary and non-linear signals,but when a short signal,such as a hydraulic impact signal,is concerned,their decomposition accuracy become very poor.An improve EEMD is proposed specifically for short hydraulic impact signals.The improvements of this new EEMD are mainly reflected in four aspects,including self-adaptive de-noising based on EEMD,signal extension based on SVM(support vector machine),extreme center fitting based on cubic spline interpolation,and pseudo component exclusion based on cross-correlation analysis.After the energy eigenvector is extracted from the result of the improved EEMD,the fault pattern recognition based on SVM with small amount of low-dimensional training samples is studied.At last,the diagnosis ability of improved EEMD+SVM method is compared with the EEMD+SVM and EMD+SVM methods,and its diagnosis accuracy is distinctly higher than the other two methods no matter the dimension of the eigenvectors are low or high.The improved EEMD is very propitious for the decomposition of short signal,such as hydraulic impact signal,and its combination with SVM has high ability for the diagnosis of hydraulic impact faults.展开更多
China＇s first interest rate hike during the last decade, aiming to cool down the seemingly overheated real estate market, had aroused more caution on housing market. This paper aims to analyze the housing price dynam...China＇s first interest rate hike during the last decade, aiming to cool down the seemingly overheated real estate market, had aroused more caution on housing market. This paper aims to analyze the housing price dynamics after an unanticipated economic shock, which was believed to have similar properties with the backward-looking expecta- tion models. The analysis of the housing price dynamics is based on the cobweb model with a simple user cost affected demand and a stock-flow supply assumption. Several nth- order delay rational difference equations are set up to illustrate the properties of housing dynamics phenomena, such as the equilibrium or oscillations, overshoot or undershoot and convergent or divergent, for a kind of heterogeneous backward-looking expectation models. The results show that demand elasticity is less than supply elasticity is not a necessary condition for the occurrence of oscillation. The housing price dynamics will vary substantially with the heterogeneous backward-looking expectation assumption and some other endogenous factors.展开更多
Numerical diffusion or filter are used in most numerical models in order to eliminate small-scale (near two-grid intervals in wavelength) waves, However, conventional diffusion or filter schemes introduce the noise, a...Numerical diffusion or filter are used in most numerical models in order to eliminate small-scale (near two-grid intervals in wavelength) waves, However, conventional diffusion or filter schemes introduce the noise, and indeed few people realized, by filters themselves. For instance, most filters are troubled when they are put to use on meteorological fields with sharp gradient or with steep slope and consequently, the recurrence of undesirable numerical high-frequent oscillations (overshooting and undershooting) seems to be inevitable, Particularly when diffusion or filter is implemented in limited-area models, serious side effects on the limited-area boundaries often contaminate the modeling results. The merits and demerits are surveyed for commonly used diffusion or filter operations. A new type of monotonic digit filter is suggested to prevent overshooting and undershooting (due to the computational shock and Gibbs oscillation) nearby the discontinuous or nearly discontinuous locations when the filtering process was carried out, meanwhile the high selective property of damping is retained. Moreover, the new filter is designed on the implicit framework so that it can easily handle the problem of boundary diminishing in limited-area modeling.展开更多
There are overshoot and undershoot phenomenon and end swing phenomenon in the cubic spline fitting in Hil- bert-Huang transform. The two problems influence data quality of the empirical mode decomposition seriously. T...There are overshoot and undershoot phenomenon and end swing phenomenon in the cubic spline fitting in Hil- bert-Huang transform. The two problems influence data quality of the empirical mode decomposition seriously. The cubic spline fitting has been analysed, and the causes of producing the overshoot and undershoot phenomenon and the end swing phenomenon have been pointed out in this paper. Two new methods of cubic spline fitting and sine spline fitting and the new technique of handling the end points of the original data curve can completely re- move the overshoot and undershoot phenomenon and the end swing phenomenon on the condition of unchanging original data, and have the advantages of the continuous fitting functions and its continuous one order derivative, the simple and convenient calculations, the small calculation amount and the easy work on it.展开更多
To suppress the overshoots and undershoots in the envelope fitting for empirical mode decomposition （EMD）, an alternative cubic spline interpolation method without overshooting and undershooting is proposed. On the ...To suppress the overshoots and undershoots in the envelope fitting for empirical mode decomposition （EMD）, an alternative cubic spline interpolation method without overshooting and undershooting is proposed. On the basis of the derived slope constraints of knots of a non-overshooting and non-undershooting cubic interpolant, together with ＂not-a-knot＂ conditions the cubic spline interpolants are constructed by replacing the requirement for equal second order derivatives at every knot with Brodlie＇ s derivative formula. Analysis and simulation experiments show that this approach can effectively avoid generating new extrema, shifting or exaggerating the existing ones in a signal, and thus significantly improve the decomposition performance of EMD.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51175511,61472444)Jiangsu Provincial Natural Science Foundation of China(Grant No.BK20150724)Pre-study Foundation of PLA University of Science and Technology,China(Grant No.KYGYZL139)
文摘The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors,however the characteristics of the signal need to be extracted accurately.Although the existing EMD(empirical mode decomposition)and EEMD(ensemble empirical mode decomposition)are suitable for processing non-stationary and non-linear signals,but when a short signal,such as a hydraulic impact signal,is concerned,their decomposition accuracy become very poor.An improve EEMD is proposed specifically for short hydraulic impact signals.The improvements of this new EEMD are mainly reflected in four aspects,including self-adaptive de-noising based on EEMD,signal extension based on SVM(support vector machine),extreme center fitting based on cubic spline interpolation,and pseudo component exclusion based on cross-correlation analysis.After the energy eigenvector is extracted from the result of the improved EEMD,the fault pattern recognition based on SVM with small amount of low-dimensional training samples is studied.At last,the diagnosis ability of improved EEMD+SVM method is compared with the EEMD+SVM and EMD+SVM methods,and its diagnosis accuracy is distinctly higher than the other two methods no matter the dimension of the eigenvectors are low or high.The improved EEMD is very propitious for the decomposition of short signal,such as hydraulic impact signal,and its combination with SVM has high ability for the diagnosis of hydraulic impact faults.
文摘China＇s first interest rate hike during the last decade, aiming to cool down the seemingly overheated real estate market, had aroused more caution on housing market. This paper aims to analyze the housing price dynamics after an unanticipated economic shock, which was believed to have similar properties with the backward-looking expecta- tion models. The analysis of the housing price dynamics is based on the cobweb model with a simple user cost affected demand and a stock-flow supply assumption. Several nth- order delay rational difference equations are set up to illustrate the properties of housing dynamics phenomena, such as the equilibrium or oscillations, overshoot or undershoot and convergent or divergent, for a kind of heterogeneous backward-looking expectation models. The results show that demand elasticity is less than supply elasticity is not a necessary condition for the occurrence of oscillation. The housing price dynamics will vary substantially with the heterogeneous backward-looking expectation assumption and some other endogenous factors.
基金the Project of Natural Science Foundation of Jiangsu Province, BK99020 and the "973' Project of "CHERES" Gl998040907 the Natio
文摘Numerical diffusion or filter are used in most numerical models in order to eliminate small-scale (near two-grid intervals in wavelength) waves, However, conventional diffusion or filter schemes introduce the noise, and indeed few people realized, by filters themselves. For instance, most filters are troubled when they are put to use on meteorological fields with sharp gradient or with steep slope and consequently, the recurrence of undesirable numerical high-frequent oscillations (overshooting and undershooting) seems to be inevitable, Particularly when diffusion or filter is implemented in limited-area models, serious side effects on the limited-area boundaries often contaminate the modeling results. The merits and demerits are surveyed for commonly used diffusion or filter operations. A new type of monotonic digit filter is suggested to prevent overshooting and undershooting (due to the computational shock and Gibbs oscillation) nearby the discontinuous or nearly discontinuous locations when the filtering process was carried out, meanwhile the high selective property of damping is retained. Moreover, the new filter is designed on the implicit framework so that it can easily handle the problem of boundary diminishing in limited-area modeling.
基金The Foundation Research and Development Programs of China (2004CB418404).
文摘There are overshoot and undershoot phenomenon and end swing phenomenon in the cubic spline fitting in Hil- bert-Huang transform. The two problems influence data quality of the empirical mode decomposition seriously. The cubic spline fitting has been analysed, and the causes of producing the overshoot and undershoot phenomenon and the end swing phenomenon have been pointed out in this paper. Two new methods of cubic spline fitting and sine spline fitting and the new technique of handling the end points of the original data curve can completely re- move the overshoot and undershoot phenomenon and the end swing phenomenon on the condition of unchanging original data, and have the advantages of the continuous fitting functions and its continuous one order derivative, the simple and convenient calculations, the small calculation amount and the easy work on it.
基金the Ministerial Level Advanced Research Foundation (445030705QB0301)
文摘To suppress the overshoots and undershoots in the envelope fitting for empirical mode decomposition （EMD）, an alternative cubic spline interpolation method without overshooting and undershooting is proposed. On the basis of the derived slope constraints of knots of a non-overshooting and non-undershooting cubic interpolant, together with ＂not-a-knot＂ conditions the cubic spline interpolants are constructed by replacing the requirement for equal second order derivatives at every knot with Brodlie＇ s derivative formula. Analysis and simulation experiments show that this approach can effectively avoid generating new extrema, shifting or exaggerating the existing ones in a signal, and thus significantly improve the decomposition performance of EMD.
