有效的射频干扰(Radio frequency interference,RFI)抑制技术是超宽带合成孔径雷达(Ul-tra-wideband synthetic aperture radar,UWB-SAR)成像质量的重要保证。通过对超宽带回波信号的特性分析,得出RFI具有短时间内平稳的特性,这样便可...有效的射频干扰(Radio frequency interference,RFI)抑制技术是超宽带合成孔径雷达(Ul-tra-wideband synthetic aperture radar,UWB-SAR)成像质量的重要保证。通过对超宽带回波信号的特性分析,得出RFI具有短时间内平稳的特性,这样便可借助谱估计方法对其进行估计。旋转不变技术估计信号参数方法(Estimation of signal parameters via rotational invariance techniques,ESPRIT)是谱估计中一种频率估计性能较好、运算量较小的方法,文章对该算法在UWB-SAR RFI抑制中的应用进行了研究分析,并通过仿真实验表明该算法对RFI具有良好的抑制性能。展开更多
To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. ...To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).展开更多
This paper presents a novel method for inferring the odor based on neural activities observed from rats' main olfactory bulbs.Multi-channel extra-cellular single unit recordings are done by micro-wire electrodes(T...This paper presents a novel method for inferring the odor based on neural activities observed from rats' main olfactory bulbs.Multi-channel extra-cellular single unit recordings are done by micro-wire electrodes(Tungsten,50 μm,32 channels)implanted in the mitral/tufted cell layers of the main olfactory bulb of the anesthetized rats to obtain neural responses to various odors.Neural responses as a key feature are measured by subtraction firing rates before stimulus from after.For odor inference,a decoding method is developed based on the ML estimation.The results show that the average decoding accuracy is about 100.0%,96.0%,and 80.0% with three rats,respectively.This work has profound implications for a novel brain-machine interface system for odor inference.展开更多
This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forec...This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forecast of transportation nodes impendence and travel time on network links. Forecasting period is two hours and the estimation is based on historical data and real time data on traffic conditions. Travel time estimation combines multivariate regression, principal component analysis, KNN （k-nearest neighbours）, cross validation and EWMA （exponentially weighted moving average） methods. When comparing estimation methodologies, relevantly better results were achieved by KNN method than with EWMA method. This is true for every time interval considered except for evening time interval when signalized arterial roads were uncongested.展开更多
Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed b...Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.展开更多
This paper provides a method to infer finger flexing motions using a 4-channel surface Electronyogram （sEMG）. Surface EMGs are hannless to the humnan body and easily done. However, they do not reflect the activity o...This paper provides a method to infer finger flexing motions using a 4-channel surface Electronyogram （sEMG）. Surface EMGs are hannless to the humnan body and easily done. However, they do not reflect the activity of specific nerves or muscles, unlike invasive EMCs. On the other hand, the non-invasive type is difficult to use for discriminating various motions while using only a small number of electrodes. Surface EMG data in this study were obtained from four electodes placed around the forearm. The motions were the flexion of each 5 single fingers （thumb, index finger, middle finger, ring finger, and little fingers）. One subject was trained with these motions and another left was untrained. The maximum likelihood estimation method was used to infer the finger motion. Experimental results have showed that this method could be useful for recognizing finger motions.The average accuracy was as high as 95%.展开更多
文摘有效的射频干扰(Radio frequency interference,RFI)抑制技术是超宽带合成孔径雷达(Ul-tra-wideband synthetic aperture radar,UWB-SAR)成像质量的重要保证。通过对超宽带回波信号的特性分析,得出RFI具有短时间内平稳的特性,这样便可借助谱估计方法对其进行估计。旋转不变技术估计信号参数方法(Estimation of signal parameters via rotational invariance techniques,ESPRIT)是谱估计中一种频率估计性能较好、运算量较小的方法,文章对该算法在UWB-SAR RFI抑制中的应用进行了研究分析,并通过仿真实验表明该算法对RFI具有良好的抑制性能。
基金supported by Joint Foundation of and China Academy of Engineering Physical (10676006)
文摘To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).
基金supported by the MKE(The Ministry of Knowledge Economy,Korea)theITRC(Information Technology Research Center)support program(NIPA-2010-C1090-1021-0010)
文摘This paper presents a novel method for inferring the odor based on neural activities observed from rats' main olfactory bulbs.Multi-channel extra-cellular single unit recordings are done by micro-wire electrodes(Tungsten,50 μm,32 channels)implanted in the mitral/tufted cell layers of the main olfactory bulb of the anesthetized rats to obtain neural responses to various odors.Neural responses as a key feature are measured by subtraction firing rates before stimulus from after.For odor inference,a decoding method is developed based on the ML estimation.The results show that the average decoding accuracy is about 100.0%,96.0%,and 80.0% with three rats,respectively.This work has profound implications for a novel brain-machine interface system for odor inference.
文摘This paper describes procedure for estimation of travel time on signalized arterial roads based on multiple data sources with application of dimensionality reduction. Travel time estimation approach incorporates forecast of transportation nodes impendence and travel time on network links. Forecasting period is two hours and the estimation is based on historical data and real time data on traffic conditions. Travel time estimation combines multivariate regression, principal component analysis, KNN （k-nearest neighbours）, cross validation and EWMA （exponentially weighted moving average） methods. When comparing estimation methodologies, relevantly better results were achieved by KNN method than with EWMA method. This is true for every time interval considered except for evening time interval when signalized arterial roads were uncongested.
基金Supported by the National Natural Science Foundation of China(No.51204145)Natural Science Foundation of Hebei Province of China(No.2013203300)
文摘Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.
基金supported by the The Ministry of Knowledge Economy,Koreaunder the ITRC(Information Technology Research Center)support programsupervised by the ⅡTA(Institute for Information Technology Advancement)ⅡTA-2008-C1090-0803-0006
文摘This paper provides a method to infer finger flexing motions using a 4-channel surface Electronyogram （sEMG）. Surface EMGs are hannless to the humnan body and easily done. However, they do not reflect the activity of specific nerves or muscles, unlike invasive EMCs. On the other hand, the non-invasive type is difficult to use for discriminating various motions while using only a small number of electrodes. Surface EMG data in this study were obtained from four electodes placed around the forearm. The motions were the flexion of each 5 single fingers （thumb, index finger, middle finger, ring finger, and little fingers）. One subject was trained with these motions and another left was untrained. The maximum likelihood estimation method was used to infer the finger motion. Experimental results have showed that this method could be useful for recognizing finger motions.The average accuracy was as high as 95%.
