Face recognition has been widely used and developed rapidly in recent years.The methods based on sparse representation have made great breakthroughs,and collaborative representation-based classification(CRC)is the typ...Face recognition has been widely used and developed rapidly in recent years.The methods based on sparse representation have made great breakthroughs,and collaborative representation-based classification(CRC)is the typical representative.However,CRC cannot distinguish similar samples well,leading to a wrong classification easily.As an improved method based on CRC,the two-phase test sample sparse representation(TPTSSR)removes the samples that make little contribution to the representation of the testing sample.Nevertheless,only one removal is not sufficient,since some useless samples may still be retained,along with some useful samples maybe being removed randomly.In this work,a novel classifier,called discriminative sparse parameter(DSP)classifier with iterative removal,is proposed for face recognition.The proposed DSP classifier utilizes sparse parameter to measure the representation ability of training samples straight-forward.Moreover,to avoid some useful samples being removed randomly with only one removal,DSP classifier removes most uncorrelated samples gradually with iterations.Extensive experiments on different typical poses,expressions and noisy face datasets are conducted to assess the performance of the proposed DSP classifier.The experimental results demonstrate that DSP classifier achieves a better recognition rate than the well-known SRC,CRC,RRC,RCR,SRMVS,RFSR and TPTSSR classifiers for face recognition in various situations.展开更多
This paper analyzes the changing trends of the Lower Yellow River(LYR)transverse profile parameters and their aberrance points by the time series analysis method.Research results show that there has been a trend of ch...This paper analyzes the changing trends of the Lower Yellow River(LYR)transverse profile parameters and their aberrance points by the time series analysis method.Research results show that there has been a trend of changes in the LYR channel transverse profile parameters since the 1950s.The main river channel has a tendency of shrinkage year by year and the trend will be continued in the future.The main features of the LYR channel shrinkage are remarkable reductions of bankfull dis-charges and bankfull areas,corresponding decreases of bankfull widths,average bankfull water depths and maximal bankfull water depths,as well as increases of bankfull water levels and width-depth ratios accompanied.The discriminant parameters for threshold of the LYR main channel shrinkage were put forward.It indicates that the LYR main channel began to shrink in the 1970s and has entered into a serious phase of channel shrinkage since the 1990s.The incompatible index of discharged water-sediment processes of the Sanmenxia Reservoir was introduced,which revealed that there was a trend of increasing in the incompatibility between water flow and sediment load.Response relations between the LYR main channel shrinkage parameters and discharged water-sediment processes of the Sanmenxia Reservoir were founded,which indicate that the LYR main channel shrinkage can be mitigated and improved through the regulation of discharged water-sediment processes of the reservoir,especially through the regulation of water-sediment incompatible index.The LYR channel for water and sediment transportation can be restored and maintained.展开更多
基金Project(2019JJ40047)supported by the Hunan Provincial Natural Science Foundation of ChinaProject(kq2014057)supported by the Changsha Municipal Natural Science Foundation,China。
文摘Face recognition has been widely used and developed rapidly in recent years.The methods based on sparse representation have made great breakthroughs,and collaborative representation-based classification(CRC)is the typical representative.However,CRC cannot distinguish similar samples well,leading to a wrong classification easily.As an improved method based on CRC,the two-phase test sample sparse representation(TPTSSR)removes the samples that make little contribution to the representation of the testing sample.Nevertheless,only one removal is not sufficient,since some useless samples may still be retained,along with some useful samples maybe being removed randomly.In this work,a novel classifier,called discriminative sparse parameter(DSP)classifier with iterative removal,is proposed for face recognition.The proposed DSP classifier utilizes sparse parameter to measure the representation ability of training samples straight-forward.Moreover,to avoid some useful samples being removed randomly with only one removal,DSP classifier removes most uncorrelated samples gradually with iterations.Extensive experiments on different typical poses,expressions and noisy face datasets are conducted to assess the performance of the proposed DSP classifier.The experimental results demonstrate that DSP classifier achieves a better recognition rate than the well-known SRC,CRC,RRC,RCR,SRMVS,RFSR and TPTSSR classifiers for face recognition in various situations.
文摘This paper analyzes the changing trends of the Lower Yellow River(LYR)transverse profile parameters and their aberrance points by the time series analysis method.Research results show that there has been a trend of changes in the LYR channel transverse profile parameters since the 1950s.The main river channel has a tendency of shrinkage year by year and the trend will be continued in the future.The main features of the LYR channel shrinkage are remarkable reductions of bankfull dis-charges and bankfull areas,corresponding decreases of bankfull widths,average bankfull water depths and maximal bankfull water depths,as well as increases of bankfull water levels and width-depth ratios accompanied.The discriminant parameters for threshold of the LYR main channel shrinkage were put forward.It indicates that the LYR main channel began to shrink in the 1970s and has entered into a serious phase of channel shrinkage since the 1990s.The incompatible index of discharged water-sediment processes of the Sanmenxia Reservoir was introduced,which revealed that there was a trend of increasing in the incompatibility between water flow and sediment load.Response relations between the LYR main channel shrinkage parameters and discharged water-sediment processes of the Sanmenxia Reservoir were founded,which indicate that the LYR main channel shrinkage can be mitigated and improved through the regulation of discharged water-sediment processes of the reservoir,especially through the regulation of water-sediment incompatible index.The LYR channel for water and sediment transportation can be restored and maintained.
