Weight matrix models for signal sequence motif are simple. A main limitation of the models is the assumption of independence between positions. Signal enhancement is achieved by taking the total likelihood as the obje...Weight matrix models for signal sequence motif are simple. A main limitation of the models is the assumption of independence between positions. Signal enhancement is achieved by taking the total likelihood as the objective function for maximization to cluster sequences into groups with different patterns. As an example, the initial and terminal signals for translation in rice genome are examined.展开更多
Integrin-mediated adhesions play critical roles in diverse cell functions. Integrins offers a platform on which mechanical stimuli, cytoskeletal organization, biochemical signals can concentrate. Mechanical stimuli tr...Integrin-mediated adhesions play critical roles in diverse cell functions. Integrins offers a platform on which mechanical stimuli, cytoskeletal organization, biochemical signals can concentrate. Mechanical stimuli transmitted by integrins influence the cytoskeleton, in turn, the cytoskeleton influences cell adhesion via integrins, then cell adhesion results in a series of signal transduction cascades. In skeleton, integrins also have a key role for bone resoption by osteoclasts and reformation by osteoblasts. In present review, the proteins involved in integrin signal transduction and integrin signal transduction pathways were discussed, mainly on the basic mechanisms of integrin signaling and the roles of integrins in bone signal transduction, which may give insight into new therapeutic agents to all kinds of skeletal diseases and new strategies for bone tissue engineering.展开更多
Aiming at the non-stationary feattwes of the roller bearing fault vibration signal, a roller bearing fault diagnosis methtxt based on improved Local Mean Decomposition (LMD) and Support Vector Machine (SVM) is pro...Aiming at the non-stationary feattwes of the roller bearing fault vibration signal, a roller bearing fault diagnosis methtxt based on improved Local Mean Decomposition (LMD) and Support Vector Machine (SVM) is proposed. In this paper, firstly, the wavelet analysis is introduced to the signal decomposition and reconstruction; secondly, the LMD method is used to decompose the recomtnion signal obtained by the wavelet analysis into a ntmaber of Product Ftmctions (PFs) that include main fault characteristics, thus, the initial feattwe vector matrixes could be formed automatically; Thirdly, by applying the Singular Valueition (SVD) techniques to the initial feature vector matrixes, the singular values of the matrixes can be obtained, which can be used as the fault feature vectors of the roller bearing and serve as the input vectors of the SVM classifier; Finally, the recognition results can be obtained from the SVM output. The results of analysis show that the propsed method can be applied to roller beating fault diagnosis effectively.展开更多
Classification of multi-dimension time series(MTS) plays an important role in knowledge discovery of time series. Many methods for MTS classification have been presented. However, most of these methods did not conside...Classification of multi-dimension time series(MTS) plays an important role in knowledge discovery of time series. Many methods for MTS classification have been presented. However, most of these methods did not consider the kind of MTS whose discriminative subsequence was not restricted to one dimension and dynamic. In order to solve the above problem, a method to extract new features with extended shapelet transformation is proposed in this study. First, key features is extracted to replace k shapelets to calculate distance, which are extracted from candidate shapelets with one class for all dimensions. Second, feature of similarity numbers as a new feature is proposed to enhance the reliability of classification. Third, because of the time-consuming searching and clustering of shapelets, distance matrix is used to reduce the computing complexity. Experiments are carried out on public dataset and the results illustrate the effectiveness of the proposed method. Moreover, anode current signals(ACS) in the aluminum reduction cell are the aforementioned MTS, and the proposed method is successfully applied to the classification of ACS.展开更多
The key of the subspace-based Direction Of Arrival (DOA) estimation lies in the estimation of signal subspace with high quality. In the case of uncorrelated signals while the signals are temporally correlated, a novel...The key of the subspace-based Direction Of Arrival (DOA) estimation lies in the estimation of signal subspace with high quality. In the case of uncorrelated signals while the signals are temporally correlated, a novel approach for the estimation of DOA in unknown correlated noise fields is proposed in this paper. The approach is based on the biorthogonality between a matrix and its Moore-Penrose pseudo inverse, and made no assumption on the spatial covariance matrix of the noise. The approach exploits the structural information of a set of spatio-temporal correlation matrices, and it can give a robust and precise estimation of signal subspace, so a precise estimation of DOA is obtained. Its performances are confirmed by computer simulation results.展开更多
The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multi...The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.展开更多
In order to solve the flow mismatch problem between pumping source output and workload demand,a novel configuration of D + A combined multi-pump controlled hydraulic system,similar to a pump-controlled system,is propo...In order to solve the flow mismatch problem between pumping source output and workload demand,a novel configuration of D + A combined multi-pump controlled hydraulic system,similar to a pump-controlled system,is proposed for a large power hydraulic system in this study. This novel configuration consists of several parallel fixed displacement pumps of different sizes and proportional variable displacement pumps,which is controlled by digital signal( on/off) and analog signal respectively( D + A pumps). The system flow is divided into two parts,one is the total flow from fixed displacement pumps,and the other is the rest desired flow supplied by variable displacement pumps to smooth and improve the demand flow. First,basic design principles and evaluation indicators of the proposed system are introduced. Then,a flow state matrix of the binary-coding digital pumps( 1: 2: 4) is obtained to provide the control signals of pumps. Experimental results show that the system output flow tracks well with acceptable flow deviation,though a little lag behind input signal.展开更多
Most of the existing algorithms for blind sources separation have a limitation that sources are statistically independent. However, in many practical applications, the source signals are non- negative and mutual stati...Most of the existing algorithms for blind sources separation have a limitation that sources are statistically independent. However, in many practical applications, the source signals are non- negative and mutual statistically dependent signals. When the observations are nonnegative linear combinations of nonnegative sources, the correlation coefficients of the observations are larger than these of source signals. In this letter, a novel Nonnegative Matrix Factorization (NMF) algorithm with least correlated component constraints to blind separation of convolutive mixed sources is proposed. The algorithm relaxes the source independence assumption and has low-complexity algebraic com- putations. Simulation results on blind source separation including real face image data indicate that the sources can be successfully recovered with the algorithm.展开更多
In this paper, the asymptotic sum rate of a multi-user distributed antenna system (DAS) is analyzed. To mitigate inter-user interference, minimum mean squared error (MMSE) receivers are utilized to cooperatively p...In this paper, the asymptotic sum rate of a multi-user distributed antenna system (DAS) is analyzed. To mitigate inter-user interference, minimum mean squared error (MMSE) receivers are utilized to cooperatively process received signals in the uplink. It shows that inter-user interference is efficiently mitigated and the uplink sum rate of a multi-user DAS is greatly improved by adopting MMSE receivers. For very large number of users and remote antennas, the asymptotic uplink sum rate of MMSE receivers is derived by using virtue of the random matrix theory, which can be The approximation is verified to be quite accurate by Monte Carlo simply calculated in an iterative way simulations.展开更多
We propose a novel flow measurement method for gas–liquid two-phase slug flow by using the blind source separation technique. The flow measurement model is established based on the fluctuation characteristics of diff...We propose a novel flow measurement method for gas–liquid two-phase slug flow by using the blind source separation technique. The flow measurement model is established based on the fluctuation characteristics of differential pressure(DP) signals measured from a Venturi meter. It is demonstrated that DP signals of two-phase flow are a linear mixture of DP signals of single phase fluids. The measurement model is a combination of throttle relationship and blind source separation model. In addition, we estimate the mixture matrix using the independent component analysis(ICA) technique. The mixture matrix could be described using the variances of two DP signals acquired from two Venturi meters. The validity of the proposed model was tested in the gas–liquid twophase flow loop facility. Experimental results showed that for most slug flow the relative error is within 10%.We also find that the mixture matrix is beneficial to investigate the flow mechanism of gas–liquid two-phase flow.展开更多
基金the Special Funds for Major National Basic Research Projects,国家自然科学基金,Research Project 248 of Beijing
文摘Weight matrix models for signal sequence motif are simple. A main limitation of the models is the assumption of independence between positions. Signal enhancement is achieved by taking the total likelihood as the objective function for maximization to cluster sequences into groups with different patterns. As an example, the initial and terminal signals for translation in rice genome are examined.
文摘Integrin-mediated adhesions play critical roles in diverse cell functions. Integrins offers a platform on which mechanical stimuli, cytoskeletal organization, biochemical signals can concentrate. Mechanical stimuli transmitted by integrins influence the cytoskeleton, in turn, the cytoskeleton influences cell adhesion via integrins, then cell adhesion results in a series of signal transduction cascades. In skeleton, integrins also have a key role for bone resoption by osteoclasts and reformation by osteoblasts. In present review, the proteins involved in integrin signal transduction and integrin signal transduction pathways were discussed, mainly on the basic mechanisms of integrin signaling and the roles of integrins in bone signal transduction, which may give insight into new therapeutic agents to all kinds of skeletal diseases and new strategies for bone tissue engineering.
基金supported by Chinese National Science Foundation Grant(No.50775068)China Postdoctoral Science Foundation funded project(No.20080430154)High-Tech Research and Development Program of China(No.2009AA04Z414)
文摘Aiming at the non-stationary feattwes of the roller bearing fault vibration signal, a roller bearing fault diagnosis methtxt based on improved Local Mean Decomposition (LMD) and Support Vector Machine (SVM) is proposed. In this paper, firstly, the wavelet analysis is introduced to the signal decomposition and reconstruction; secondly, the LMD method is used to decompose the recomtnion signal obtained by the wavelet analysis into a ntmaber of Product Ftmctions (PFs) that include main fault characteristics, thus, the initial feattwe vector matrixes could be formed automatically; Thirdly, by applying the Singular Valueition (SVD) techniques to the initial feature vector matrixes, the singular values of the matrixes can be obtained, which can be used as the fault feature vectors of the roller bearing and serve as the input vectors of the SVM classifier; Finally, the recognition results can be obtained from the SVM output. The results of analysis show that the propsed method can be applied to roller beating fault diagnosis effectively.
基金Projects(61773405,61725306,61533020)supported by the National Natural Science Foundation of ChinaProject(2018zzts583)supported by the Fundamental Research Funds for the Central Universities,China
文摘Classification of multi-dimension time series(MTS) plays an important role in knowledge discovery of time series. Many methods for MTS classification have been presented. However, most of these methods did not consider the kind of MTS whose discriminative subsequence was not restricted to one dimension and dynamic. In order to solve the above problem, a method to extract new features with extended shapelet transformation is proposed in this study. First, key features is extracted to replace k shapelets to calculate distance, which are extracted from candidate shapelets with one class for all dimensions. Second, feature of similarity numbers as a new feature is proposed to enhance the reliability of classification. Third, because of the time-consuming searching and clustering of shapelets, distance matrix is used to reduce the computing complexity. Experiments are carried out on public dataset and the results illustrate the effectiveness of the proposed method. Moreover, anode current signals(ACS) in the aluminum reduction cell are the aforementioned MTS, and the proposed method is successfully applied to the classification of ACS.
基金Supported by the National Natural Science Foundation of China(No.60372049)
文摘The key of the subspace-based Direction Of Arrival (DOA) estimation lies in the estimation of signal subspace with high quality. In the case of uncorrelated signals while the signals are temporally correlated, a novel approach for the estimation of DOA in unknown correlated noise fields is proposed in this paper. The approach is based on the biorthogonality between a matrix and its Moore-Penrose pseudo inverse, and made no assumption on the spatial covariance matrix of the noise. The approach exploits the structural information of a set of spatio-temporal correlation matrices, and it can give a robust and precise estimation of signal subspace, so a precise estimation of DOA is obtained. Its performances are confirmed by computer simulation results.
基金supported by the National Natural Science Foundation of China (61202208)
文摘The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.
基金Supported by the National Natural Science Foundation of China(No.51575471)the Key Project of Natural Science Foundation of Hebei Province(No.E2016203264)
文摘In order to solve the flow mismatch problem between pumping source output and workload demand,a novel configuration of D + A combined multi-pump controlled hydraulic system,similar to a pump-controlled system,is proposed for a large power hydraulic system in this study. This novel configuration consists of several parallel fixed displacement pumps of different sizes and proportional variable displacement pumps,which is controlled by digital signal( on/off) and analog signal respectively( D + A pumps). The system flow is divided into two parts,one is the total flow from fixed displacement pumps,and the other is the rest desired flow supplied by variable displacement pumps to smooth and improve the demand flow. First,basic design principles and evaluation indicators of the proposed system are introduced. Then,a flow state matrix of the binary-coding digital pumps( 1: 2: 4) is obtained to provide the control signals of pumps. Experimental results show that the system output flow tracks well with acceptable flow deviation,though a little lag behind input signal.
基金Supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20060280003)Shanghai Leading Academic Dis-cipline Project (T0102)
文摘Most of the existing algorithms for blind sources separation have a limitation that sources are statistically independent. However, in many practical applications, the source signals are non- negative and mutual statistically dependent signals. When the observations are nonnegative linear combinations of nonnegative sources, the correlation coefficients of the observations are larger than these of source signals. In this letter, a novel Nonnegative Matrix Factorization (NMF) algorithm with least correlated component constraints to blind separation of convolutive mixed sources is proposed. The algorithm relaxes the source independence assumption and has low-complexity algebraic com- putations. Simulation results on blind source separation including real face image data indicate that the sources can be successfully recovered with the algorithm.
文摘In this paper, the asymptotic sum rate of a multi-user distributed antenna system (DAS) is analyzed. To mitigate inter-user interference, minimum mean squared error (MMSE) receivers are utilized to cooperatively process received signals in the uplink. It shows that inter-user interference is efficiently mitigated and the uplink sum rate of a multi-user DAS is greatly improved by adopting MMSE receivers. For very large number of users and remote antennas, the asymptotic uplink sum rate of MMSE receivers is derived by using virtue of the random matrix theory, which can be The approximation is verified to be quite accurate by Monte Carlo simply calculated in an iterative way simulations.
基金Supported by the National Natural Science Foundation of China(51304231)the Natural Science Foundation of Shandong Province(ZR2010EQ015)
文摘We propose a novel flow measurement method for gas–liquid two-phase slug flow by using the blind source separation technique. The flow measurement model is established based on the fluctuation characteristics of differential pressure(DP) signals measured from a Venturi meter. It is demonstrated that DP signals of two-phase flow are a linear mixture of DP signals of single phase fluids. The measurement model is a combination of throttle relationship and blind source separation model. In addition, we estimate the mixture matrix using the independent component analysis(ICA) technique. The mixture matrix could be described using the variances of two DP signals acquired from two Venturi meters. The validity of the proposed model was tested in the gas–liquid twophase flow loop facility. Experimental results showed that for most slug flow the relative error is within 10%.We also find that the mixture matrix is beneficial to investigate the flow mechanism of gas–liquid two-phase flow.