Aim To detect sensor failure in control system using a single sensor signal. Methods A neural predictor was designed based on a radial basis function network(RBFN), and the neural predictor learned the sensor sig...Aim To detect sensor failure in control system using a single sensor signal. Methods A neural predictor was designed based on a radial basis function network(RBFN), and the neural predictor learned the sensor signal on line with a hybrid algorithm composed of n means clustering and Kalman filter and then gave the estimation of the sensor signal at the next step. If the difference between the estimation and the actural values of the sensor signal exceeded a threshold, the sensor could be declared to have a failure. The choice of the failure detection threshold depends on the noise variance and the possible prediction error of neural predictor. Results and Conclusion\ The computer simulation results show the proposed method can detect sensor failure correctly for a gyro in an automotive engine.展开更多
In order to improve the performance of voice conversion, the fundamental frequency （F0） transformation methods are investigated, and an efficient F0 transformation algorithm is proposed. First, unlike the traditiona...In order to improve the performance of voice conversion, the fundamental frequency （F0） transformation methods are investigated, and an efficient F0 transformation algorithm is proposed. First, unlike the traditional linear transformation methods, the relationships between F0s and spectral parameters are explored. In each component of the Gaussian mixture model （GMM）, the F0s are predicted from the converted spectral parameters using the support vector regression （SVR） method. Then, in order to reduce the over- smoothing caused by the statistical average of the GMM, a mixed transformation method combining SVR with the traditional mean-variance linear （MVL） conversion is presented. Meanwhile, the adaptive median filter, prevalent in image processing, is adopted to solve the discontinuity problem caused by the frame-wise transformation. Objective and subjective experiments are carried out to evaluate the performance of the proposed method. The results demonstrate that the proposed method outperforms the traditional F0 transformation methods in terms of the similarity and the quality.展开更多
Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a...Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a SVM with spline kernel function. With the help of this model, nonlinear model predictive control can be transformed to linear model predictive control, and consequently a unified analytical solution of optimal input of multi-step-ahead predictive control is possible to derive. This algorithm does not require online iterative optimization in order to be suitable for real-time control with less calculation. The simulation results of pH neutralization process and CSTR reactor show the effectiveness and advantages of the presented algorithm.展开更多
Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squ...Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squares support vector machine(LS-SVM) algorithm is an improved algorithm of SVM.But the common LS-SVM algorithm,used directly in safety predictions,has some problems.We have first studied gas prediction problems and the basic theory of LS-SVM.Given these problems,we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm,based on LS-SVM.Finally,given our observed data,we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its performance.The simulation results have verified the validity of the new algorithm.展开更多
In order to investigate the influences of caliper, formation thickness and invaded zone on the form of dual laterologs, forward modeling technique were applied to calculate the dual laterologs for different cases. The...In order to investigate the influences of caliper, formation thickness and invaded zone on the form of dual laterologs, forward modeling technique were applied to calculate the dual laterologs for different cases. The result shows that the resistivity logs become smoother and lower as the borehole diameter increases, the increase of the contrast between mud resistivity and formation resistivity induce the logs to be more pointed. When the formation thickness is less than lm, the two-peak on the logs for resistive invasion vanished, and for thickness between 1 m and 4 m, the form of logs does not vary significantly. If the formation thickness is greater than 4 m, a platform appears on the logs at the middle of the formation. The thinner the invaded zone is, the more obvious the invasion feature on the laterologs is. For thick invaded zone the form of logs tend to be that of an uninvaded resistive formation. The form and amplitude of logs depend on the resistivity contrast between invaded zone, uninvaded formation and adjacentlayers.展开更多
We study the global umbilic submanifolds with parallel mean curvature vector fields in a Riemannian manifold with quasi constant curvature and get a local pinching theorem about the length of the second fundamental form.
This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff pr...This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient （HTffOG） feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.展开更多
Objective： To validate the hypothesis that there exists an optimal axial compression stress range to enhance tibial fracture healing.Methods： Rabbits with a surgically induced V-shaped tibial fracture were separated...Objective： To validate the hypothesis that there exists an optimal axial compression stress range to enhance tibial fracture healing.Methods： Rabbits with a surgically induced V-shaped tibial fracture were separated into 2 main groups： the control group （C Group, n=6） without application of any axial compression stress stimulation postoperatively and the stimulation group （ S Group, n=90）. The S Group was further divided into 20 subgroups （S11 to S54） in terms of 5 axial compression stress stimulation levels （112.8 kPa, 289.8kPa, 396.5 kPa, 472.7 kPa, and 602.3 kPa） and 4 experimental endpoints （1, 3, 5 and 8 weeks after operation）. A custom made circular external fixator was used to provide the axial compression stress of the fracture sites. Based on X-ray observation, a fracture healing scoring system was created to evaluate the fracture healing process.Results： At 8 weeks after operation, there existed a ＂⌒-shape＂ relationship between healing score and axial compression stress stimulation level of fracture site. The optimal axial compression stress stimulation ranged from 289.8 kPa to 472.7 kPa, accompanying the best fracture healing, i.e. the fracture line became indistinct or almost disappeared, and a lot of callus jointed the two fracture ends. Meanwhile, at 5 weeks after operation, corresponding to the relatively low healing scores, there was a fracture healing performance similar to that at 8 weeks. Besides, at 1 or 3 weeks after operation, for all the axial compression stress levels （0-602.3 kPa）, no obvious healing effect was found.Conclusions： It is implied from the stated X-ray observation results in this study that the potential optimal axial compression stress stimulation and optimal fracture healing time are available. The axial compression stress level of 289.8-472.7 kPa and fracture healing time of more than 8 weeks jointly comprise the optimal axial compression stress stimulation conditions to enhance tibial fracture healing.展开更多
An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into...An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into wavelet technique in support vector machine(SVM).Since manifold wavelet function can yield features that describe of the stock time series both at various locations and at varying time granularities,the MWSVM can approximate arbitrary nonlinear functions and forecast stock returns accurately.The applicability and validity of MWSVM for stock returns forecasting is confirmed through experiments on real-world stock data.展开更多
文摘Aim To detect sensor failure in control system using a single sensor signal. Methods A neural predictor was designed based on a radial basis function network(RBFN), and the neural predictor learned the sensor signal on line with a hybrid algorithm composed of n means clustering and Kalman filter and then gave the estimation of the sensor signal at the next step. If the difference between the estimation and the actural values of the sensor signal exceeded a threshold, the sensor could be declared to have a failure. The choice of the failure detection threshold depends on the noise variance and the possible prediction error of neural predictor. Results and Conclusion\ The computer simulation results show the proposed method can detect sensor failure correctly for a gyro in an automotive engine.
基金The National Natural Science Foundation of China(No. 60975017)the Natural Science Foundation of Guangdong Province (No. 10252800001000001)the Natural Science Foundation of Higher Education Institutions of Jiangsu Province (No. 10KJB510005)
文摘In order to improve the performance of voice conversion, the fundamental frequency （F0） transformation methods are investigated, and an efficient F0 transformation algorithm is proposed. First, unlike the traditional linear transformation methods, the relationships between F0s and spectral parameters are explored. In each component of the Gaussian mixture model （GMM）, the F0s are predicted from the converted spectral parameters using the support vector regression （SVR） method. Then, in order to reduce the over- smoothing caused by the statistical average of the GMM, a mixed transformation method combining SVR with the traditional mean-variance linear （MVL） conversion is presented. Meanwhile, the adaptive median filter, prevalent in image processing, is adopted to solve the discontinuity problem caused by the frame-wise transformation. Objective and subjective experiments are carried out to evaluate the performance of the proposed method. The results demonstrate that the proposed method outperforms the traditional F0 transformation methods in terms of the similarity and the quality.
基金Supported by the State Key Development Program for Basic Research of China （No.2002CB312200） and the National Natural Science Foundation of China （No.60574019）.
文摘Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a SVM with spline kernel function. With the help of this model, nonlinear model predictive control can be transformed to linear model predictive control, and consequently a unified analytical solution of optimal input of multi-step-ahead predictive control is possible to derive. This algorithm does not require online iterative optimization in order to be suitable for real-time control with less calculation. The simulation results of pH neutralization process and CSTR reactor show the effectiveness and advantages of the presented algorithm.
文摘Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squares support vector machine(LS-SVM) algorithm is an improved algorithm of SVM.But the common LS-SVM algorithm,used directly in safety predictions,has some problems.We have first studied gas prediction problems and the basic theory of LS-SVM.Given these problems,we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm,based on LS-SVM.Finally,given our observed data,we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its performance.The simulation results have verified the validity of the new algorithm.
文摘In order to investigate the influences of caliper, formation thickness and invaded zone on the form of dual laterologs, forward modeling technique were applied to calculate the dual laterologs for different cases. The result shows that the resistivity logs become smoother and lower as the borehole diameter increases, the increase of the contrast between mud resistivity and formation resistivity induce the logs to be more pointed. When the formation thickness is less than lm, the two-peak on the logs for resistive invasion vanished, and for thickness between 1 m and 4 m, the form of logs does not vary significantly. If the formation thickness is greater than 4 m, a platform appears on the logs at the middle of the formation. The thinner the invaded zone is, the more obvious the invasion feature on the laterologs is. For thick invaded zone the form of logs tend to be that of an uninvaded resistive formation. The form and amplitude of logs depend on the resistivity contrast between invaded zone, uninvaded formation and adjacentlayers.
基金Supported by the Directing Research Subject of Jiangsu Education Bureau(03103146)
文摘We study the global umbilic submanifolds with parallel mean curvature vector fields in a Riemannian manifold with quasi constant curvature and get a local pinching theorem about the length of the second fundamental form.
基金Supported by the National High Technology Research and Development Program of China(No.2007AA01Z164)the National Natural Science Foundation of China(No.61273258)
文摘This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient （HTffOG） feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.
基金This work was supported by grants from the Chongqing Academician Foundation （No. 1998-93）, the National Natural Science Foundation of China （No. 30122202 and No. 30928005） and the Third Military Medical University Research Foundation （No. 2009 XHG16）,
文摘Objective： To validate the hypothesis that there exists an optimal axial compression stress range to enhance tibial fracture healing.Methods： Rabbits with a surgically induced V-shaped tibial fracture were separated into 2 main groups： the control group （C Group, n=6） without application of any axial compression stress stimulation postoperatively and the stimulation group （ S Group, n=90）. The S Group was further divided into 20 subgroups （S11 to S54） in terms of 5 axial compression stress stimulation levels （112.8 kPa, 289.8kPa, 396.5 kPa, 472.7 kPa, and 602.3 kPa） and 4 experimental endpoints （1, 3, 5 and 8 weeks after operation）. A custom made circular external fixator was used to provide the axial compression stress of the fracture sites. Based on X-ray observation, a fracture healing scoring system was created to evaluate the fracture healing process.Results： At 8 weeks after operation, there existed a ＂⌒-shape＂ relationship between healing score and axial compression stress stimulation level of fracture site. The optimal axial compression stress stimulation ranged from 289.8 kPa to 472.7 kPa, accompanying the best fracture healing, i.e. the fracture line became indistinct or almost disappeared, and a lot of callus jointed the two fracture ends. Meanwhile, at 5 weeks after operation, corresponding to the relatively low healing scores, there was a fracture healing performance similar to that at 8 weeks. Besides, at 1 or 3 weeks after operation, for all the axial compression stress levels （0-602.3 kPa）, no obvious healing effect was found.Conclusions： It is implied from the stated X-ray observation results in this study that the potential optimal axial compression stress stimulation and optimal fracture healing time are available. The axial compression stress level of 289.8-472.7 kPa and fracture healing time of more than 8 weeks jointly comprise the optimal axial compression stress stimulation conditions to enhance tibial fracture healing.
基金the Hunan Natural Science Foundation(No. 09JJ3129)the Hunan Key Social Science Foundation (No. 09ZDB04)the Hunan Social Science Foundation (No. 08JD28)
文摘An admissible manifold wavelet kernel is proposed to construct manifold wavelet support vector machine(MWSVM) for stock returns forecasting.The manifold wavelet kernel is obtained by incorporating manifold theory into wavelet technique in support vector machine(SVM).Since manifold wavelet function can yield features that describe of the stock time series both at various locations and at varying time granularities,the MWSVM can approximate arbitrary nonlinear functions and forecast stock returns accurately.The applicability and validity of MWSVM for stock returns forecasting is confirmed through experiments on real-world stock data.
