基于LBSN动态异构网络的时间感知兴趣点推荐

随着基于位置社交网络(Location-Based Social Network,LBSN)的快速发展,兴趣点(Point-Of-Interest,POI)推荐可以帮助人们发现有趣的并吸引人的位置。针对签到数据的稀疏性和用户兴趣的动态性等挑战性问题,提出了基于LBSN动态异构网络的时间感知兴趣点推荐算法。在LBSN异构网络模式中增加会话节点类型。通过动态元路径,在用户和兴趣点语义关系之间有效地融入时间信息、位置信息和社交信息等。设置了用户-兴趣点之间的动态元路径集,并提出了动态路径实例的偏好度计算方法。采用矩阵分解模型对不同动态偏好矩阵进行矩阵分解。根据不同动态元路径的用户特征矩阵和兴趣点特征矩阵,获取用户在目标时间访问兴趣点的推荐列表。实验结果表明,与其他兴趣点推荐方法相比,所提方法在兴趣点推荐精确度上取得了较好的推荐结果,具有良好的应用前景。     

裂纹数密度具有空间分布的随机介质模拟理论

利用随机过程的谱展开理论以及Hudson的裂纹介质模型，构造一种裂纹数密度具有空间统计分布的随机介质模型，给出了详细的理论推导过程。该模型利用Hudson理论的将裂纹微观参数(裂纹数密度、裂纹半径等)与裂纹介质的宏观性质(弹性常数)联系起来的特点，对可以用二维指数椭圆型、Gaussian型自相关函数描述裂纹数密度的裂纹介质，进行了二维随机介质的模拟。结果表明：(1)基于这一模拟理论的随机介质模型能灵活、有效地描述实际非均匀、各向异性裂纹介质：(2)裂纹数密度对随机裂纹介质的各个弹性常数具有不同程度的影响：(3)Gaussian型自相关函数能描述单尺度平滑的非均匀介质，而指数型随机介质具有多尺度、自相似的特性。     

基于2 维非负矩阵分解的时频图像压缩在柴油机故障诊断中的应用

针对1 维非负矩阵分解技术对2 维矩阵特征降维时,会产生数据量巨大、计算效率低下和丢失原始数据 结构信息的问题,引入2 维非负矩阵分解技术。通过S 变换得到振动信号的时频图像,用1DNMF 和2DNMF 分别 压缩时频图像,对压缩后的图像信息进行分类,对柴油机在8 种状态下的振动信号进行采集,并采用最近邻分类器、 朴素贝叶斯分类器和支持向量机分类器进行实验对比。结果表明,2 维非负矩阵分解技术比原始的1 维技术计算效 率更高,故障诊断更精准。     

Feature Extraction and Recognition for Rolling Element Bearing Fault Utilizing Short-Time Fourier Transform and Non-negative Matrix Factorization

Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, the time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classify the high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution(TFD) with non-negative matrix factorization(NMF), and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform(STFT). Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network(ANN), NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.     

转子共频相关故障源源数估计与子带盲分离

针对转子异常振动产生含交叉频率的响应,其共频相关故障源不满足统计独立要求,提出利用非负矩阵法在频域中计算故障源个数,不计及源信号和混合系统特性,可以正确估计出故障源数目或源数上限。提出利用小波包分解故障信号,选择互信息较小的子带进行重构,剔除共频信号并进行盲分离,得到独立非相关的源信号,保留了故障信息。理论及实验结果证明了所提出方法的有效性。     

On robustness in the gap metric and coprime factor uncertainty for LTV systems

In this paper, we study the problem of robust stabilization for discrete linear time-varying (LTV) systems subject to time-varying normalized coprime factor uncertainty. Operator theoretic results which generalize similar results known to hold for linear time-invariant (infinite-dimensional) systems are developed. In particular, we compute an upper bound for the maximal achievable stability margin under TV normalized coprime factor uncertainty in terms of the norm of an operator with a time-varying Hankel structure. We point to a necessary and sufficient condition which guarantees compactness of the TV Hankel operator, and in which case singular values and vectors can be used to compute the time-varying stability margin and TV controller.     

Decomposition of singular large sparse matrix by adding dummy links and dummy degrees

Abstract

This paper proposes a simple scheme to decompose an n×n nonpositive definite matrix, A, associated with simultaneous equations, A X = B, into a triple‐factors (lower triangular, diagonal, and upper triangular matrices), i.e., Å = L D U, without interchanging rows or columns of A, but with A expanded with new rows and new columns to an m×m matrix Å. Whenever a near‐zero diagonal element, say ā_ii , is encountered and used as a pivoting element, an appropriate positive real number, say p, is added to this diagonal element, and a new term —px_k is also added to the i‐th equation, where x_k is a new variable called “dummy variable'’. If we also add a new equation —px_i + px_k = 0 to enforce the new added variable x_k equal to x_i then the modified i‐th equation has the same effect as the original equation. Therefore, the original solution X can be found directly from the expanded solution of the modified expanded equation. The method is very useful in solving the following problems: (1) nonlinear problems near the limit state, (2) postbuckling analysis, (3) system equations with constraint conditions, and (4) getting eigenvectors from eigenvalues.     

A numerical reconstruction method in inverse elastic scattering

In this paper a new numerical method for the shape reconstruction of obstacles in elastic scattering is proposed. Initially, the direct scattering problem for a rigid body and the mathematical setting for the corresponding inverse one are presented. Inverse uniqueness issues for the general case of mixed boundary conditions on the boundary of our obstacle, which are valid for a rigid body as well are established. The inversion algorithm based on the factorization method is presented into a suitable form and a new numerical scheme for the reconstruction of the shape of the scatterer, using far-field measurements, is given. In particular, an efficient Tikhonov parameter choice technique, called Improved Maximum Product Criterion (IMPC) and its linchpin within the framework of the factorization method is exploited. Our regularization parameter is computed via a fast iterative algorithm which requires no a priori knowledge of the noise level in the far-field data. Finally, the effectiveness of IMPC is illustrated with various numerical examples involving a kite, an acorn, and a peanut-shaped object.