Ground-based interferometric synthetic aperture radar(GB-InSAR)can take deformation measurement with a high accuracy.Partition of the GB-InSAR deformation map benefits analyzing the deformation state of the monitoring...Ground-based interferometric synthetic aperture radar(GB-InSAR)can take deformation measurement with a high accuracy.Partition of the GB-InSAR deformation map benefits analyzing the deformation state of the monitoring scene better.Existing partition methods rely on labelled datasets or single deformation feature,and they cannot be effectively utilized in GBInSAR applications.This paper proposes an improved partition method of the GB-InSAR deformation map based on dynamic time warping(DTW)and k-means.The DTW similarities between a reference point and all the measurement points are calculated based on their time-series deformations.Then the DTW similarity and cumulative deformation are taken as two partition features.With the k-means algorithm and the score based on multi evaluation indexes,a deformation map can be partitioned into an appropriate number of classes.Experimental datasets of West Copper Mine are processed to validate the effectiveness of the proposed method,whose measurement points are divided into seven classes with a score of 0.3151.展开更多
The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are ...The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.展开更多
Aiming at the diversity of hand gesture traces by different people,the article presents novel method called cluster dynamic time warping( CDTW),which is based on the main axis classification and sample clustering of i...Aiming at the diversity of hand gesture traces by different people,the article presents novel method called cluster dynamic time warping( CDTW),which is based on the main axis classification and sample clustering of individuals. This method shows good performance on reducing the complexity of recognition and strong robustness of individuals. Data acquisition is implemented on a triaxial accelerometer with 100 Hz sampling frequency. A database of 2400 traces was created by ten subjects for the system testing and evaluation. The overall accuracy was found to be 98. 84% for user independent gesture recognition and 96. 7% for user dependent gesture recognition,higher than dynamic time warping( DTW),derivative DTW( DDTW) and piecewise DTW( PDTW) methods.Computation cost of CDTW in this project has been reduced 11 520 times compared with DTW.展开更多
The use of dead reckoning and fngerprint matching for navigation is a widespread technical method.However,fngerprint mismatching and low fusion accuracy are prevalent issues in indoor navigation systems.This work pres...The use of dead reckoning and fngerprint matching for navigation is a widespread technical method.However,fngerprint mismatching and low fusion accuracy are prevalent issues in indoor navigation systems.This work presents an improved dynamic time warping and a chicken particle flter to handle these two challenges.To generate the Horizontal and Vertical(HV)fngerprint,the pitch and roll are employed instead of the original fngerprint intensity to extract the horizontal and vertical components of the magnetic feld fngerprint.Derivative dynamic time warping employs the HV fngerprint in its derivative form,which receives higher-level features because of the consideration of fngerprint shape information.Chicken Swarm Optimization(CSO)is used to enhance particle weights,which minimizes position error to tackle the particle impoverishment problem for a fusion navigation system.The results of the experiments suggest that the enhanced algorithm can improve indoor navigation accuracy signifcantly.展开更多
大部分系统使用深度学习技术完成语音识别任务,并取得良好的效果。但是,基于深度学习的语音识别技术对计算机硬件算力的要求较高,同时需要大量的语音样本对语音识别模型进行训练。针对这些问题,基于改进后的动态时间归整(Dynamic Time W...大部分系统使用深度学习技术完成语音识别任务,并取得良好的效果。但是,基于深度学习的语音识别技术对计算机硬件算力的要求较高,同时需要大量的语音样本对语音识别模型进行训练。针对这些问题,基于改进后的动态时间归整(Dynamic Time Warping,DTW)算法设计并实现了一个语音识别系统。展开更多
采用基于动态规划方法的动态时间归正技术DTW(D YNAM IC T IM E W ARP ING),可成功解决语音信号特征参数序列比较时时长不等的问题.在基于DTW的特征匹配用改进的动态时间归正方法将模板特征序列和语音特征序列进行匹配的基础上,比较两...采用基于动态规划方法的动态时间归正技术DTW(D YNAM IC T IM E W ARP ING),可成功解决语音信号特征参数序列比较时时长不等的问题.在基于DTW的特征匹配用改进的动态时间归正方法将模板特征序列和语音特征序列进行匹配的基础上,比较两者之间的失真,得出识别判决的依据.实验表明,改进后的算法在孤立词语音识别中获得了良好性能.展开更多
基金supported by the National Natural Science Foundation of China(61971037,61960206009,61601031)the Natural Science Foundation of Chongqing,China(cstc2020jcyj-msxm X0608,cstc2020jcyj-jq X0008)。
文摘Ground-based interferometric synthetic aperture radar(GB-InSAR)can take deformation measurement with a high accuracy.Partition of the GB-InSAR deformation map benefits analyzing the deformation state of the monitoring scene better.Existing partition methods rely on labelled datasets or single deformation feature,and they cannot be effectively utilized in GBInSAR applications.This paper proposes an improved partition method of the GB-InSAR deformation map based on dynamic time warping(DTW)and k-means.The DTW similarities between a reference point and all the measurement points are calculated based on their time-series deformations.Then the DTW similarity and cumulative deformation are taken as two partition features.With the k-means algorithm and the score based on multi evaluation indexes,a deformation map can be partitioned into an appropriate number of classes.Experimental datasets of West Copper Mine are processed to validate the effectiveness of the proposed method,whose measurement points are divided into seven classes with a score of 0.3151.
基金supported by the National Natural Science Foundation of China(6153302061309014)the Natural Science Foundation Project of CQ CSTC(cstc2017jcyj AX0408)
文摘The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.
基金National Key R&D Program of China(No.2016YFB1001401)
文摘Aiming at the diversity of hand gesture traces by different people,the article presents novel method called cluster dynamic time warping( CDTW),which is based on the main axis classification and sample clustering of individuals. This method shows good performance on reducing the complexity of recognition and strong robustness of individuals. Data acquisition is implemented on a triaxial accelerometer with 100 Hz sampling frequency. A database of 2400 traces was created by ten subjects for the system testing and evaluation. The overall accuracy was found to be 98. 84% for user independent gesture recognition and 96. 7% for user dependent gesture recognition,higher than dynamic time warping( DTW),derivative DTW( DDTW) and piecewise DTW( PDTW) methods.Computation cost of CDTW in this project has been reduced 11 520 times compared with DTW.
基金supported by Grant EGD21QD15,the Research project of Shanghai Polytechnic University。
文摘The use of dead reckoning and fngerprint matching for navigation is a widespread technical method.However,fngerprint mismatching and low fusion accuracy are prevalent issues in indoor navigation systems.This work presents an improved dynamic time warping and a chicken particle flter to handle these two challenges.To generate the Horizontal and Vertical(HV)fngerprint,the pitch and roll are employed instead of the original fngerprint intensity to extract the horizontal and vertical components of the magnetic feld fngerprint.Derivative dynamic time warping employs the HV fngerprint in its derivative form,which receives higher-level features because of the consideration of fngerprint shape information.Chicken Swarm Optimization(CSO)is used to enhance particle weights,which minimizes position error to tackle the particle impoverishment problem for a fusion navigation system.The results of the experiments suggest that the enhanced algorithm can improve indoor navigation accuracy signifcantly.
文摘采用基于动态规划方法的动态时间归正技术DTW(D YNAM IC T IM E W ARP ING),可成功解决语音信号特征参数序列比较时时长不等的问题.在基于DTW的特征匹配用改进的动态时间归正方法将模板特征序列和语音特征序列进行匹配的基础上,比较两者之间的失真,得出识别判决的依据.实验表明,改进后的算法在孤立词语音识别中获得了良好性能.
