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Search Results: 1 - 10 of 35807 matches for " Ming Gu "
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Subspace Iteration Randomization and Singular Value Problems
Ming Gu
Mathematics , 2014,
Abstract: A classical problem in matrix computations is the efficient and reliable approximation of a given matrix by a matrix of lower rank. The truncated singular value decomposition (SVD) is known to provide the best such approximation for any given fixed rank. However, the SVD is also known to be very costly to compute. Among the different approaches in the literature for computing low-rank approximations, randomized algorithms have attracted researchers' recent attention due to their surprising reliability and computational efficiency in different application areas. Typically, such algorithms are shown to compute with very high probability low-rank approximations that are within a constant factor from optimal, and are known to perform even better in many practical situations. In this paper, we present a novel error analysis that considers randomized algorithms within the subspace iteration framework and show with very high probability that highly accurate low-rank approximations as well as singular values can indeed be computed quickly for matrices with rapidly decaying singular values. Such matrices appear frequently in diverse application areas such as data analysis, fast structured matrix computations and fast direct methods for large sparse linear systems of equations and are the driving motivation for randomized methods. Furthermore, we show that the low-rank approximations computed by these randomized algorithms are actually rank-revealing approximations, and the special case of a rank-1 approximation can also be used to correctly estimate matrix 2-norms with very high probability. Our numerical experiments are in full support of our conclusions.
Performance Prediction Based on Statistics of Sparse Matrix-Vector Multiplication on GPUs  [PDF]
Ruixing Wang, Tongxiang Gu, Ming Li
Journal of Computer and Communications (JCC) , 2017, DOI: 10.4236/jcc.2017.56005
Abstract: As one of the most essential and important operations in linear algebra, the performance prediction of sparse matrix-vector multiplication (SpMV) on GPUs has got more and more attention in recent years. In 2012, Guo and Wang put forward a new idea to predict the performance of SpMV on GPUs. However, they didn’t consider the matrix structure completely, so the execution time predicted by their model tends to be inaccurate for general sparse matrix. To address this problem, we proposed two new similar models, which take into account the structure of the matrices and make the performance prediction model more accurate. In addition, we predict the execution time of SpMV for CSR-V, CSR-S, ELL and JAD sparse matrix storage formats by the new models on the CUDA platform. Our experimental results show that the accuracy of prediction by our models is 1.69 times better than Guo and Wang’s model on average for most general matrices.
A Pocket Signal Detector with Smart Phone for Panel  [PDF]
Xiaosong Zhu, Shaofei Qin, Ming An, Lei Gu
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2017, DOI: 10.4236/ijcns.2017.108B030
With the rapid development and widespread of communication technology, signal detection has become an important part of security checking. General equipment such as spectrum analyzer and other the same are bulky, unprofessional, not portable, and expensive. To solve these problems, a POCKET signal detection equipment that can be displayed and controlled by intelligent mobile terminal is dealt in this paper, which is flexible for using Software Defined Radio which is based on integrated single chip broadband RF front-end and adopting display and control scheme which is based on intelligent mobile phone as terminal. Besides, a display and control APP that based on Android system is developed for operating Panel.
The Lie Group Structure of the $η-ξ$ Space-time and its Physical Significance
Zhi-Ming Gu
Mathematics , 2004,
Abstract: The $\eta-\xi$ space-time is suggested by Gui for the quantum field theory in 1988. This paper consists of two parts. The first part is devoted to the discussion of the global properties of the $\eta-\xi$ space-time. The result contains a proof which asserts that the $\eta-\xi$ space-time is homeomorphic to $\mathbb{C}^{*}\times \mathbb{C}^{*}\times \mathbb{C}^{2}$ by means of two explicit maps, which shows that the $\eta-\xi$ space-time allows a Lie group structure. Thus some transformation groups, one of which is isomorphic to the Lorentz group in two dimensions, can be found. The other part of the paper is the discussion about the embedding of some subspaces in the $\eta-\xi$ space-time. In particular, it is pointed out that the Euclidean space-time and the Minkowskian space-time are linked in a way in the $\eta-\xi$ space-time such that the tilde field appears naturally. In addition some formulae in the $\eta-\xi$ space-time reappear in a more natural way.
Gaussian Elimination with Randomized Complete Pivoting
Christopher Melgaard,Ming Gu
Statistics , 2015,
Abstract: Gaussian elimination with partial pivoting (GEPP) has long been among the most widely used methods for computing the LU factorization of a given matrix. However, this method is also known to fail for matrices that induce large element growth during the factorization process. In this paper, we propose a new scheme, Gaussian elimination with randomized complete pivoting (GERCP) for the efficient and reliable LU factorization of a given matrix. GERCP satisfies GECP (Gaussian elimination with complete pivoting) style element growth bounds with high probability, yet costs only marginally higher than GEPP. Our numerical experimental results strongly suggest that GERCP is as reliable as GECP and as efficient as GEPP for computing the LU factorization.
ART-based Hierarchical Clustering Algorithm Using Quadratic Junction Neural Networks

GU Ming,

计算机科学 , 2006,
Abstract: In this paper, structure and properties of neural networks with quadratic junction are presented. Unsupervised learning rules about the neural networks are given. Using this kind of neural networks, an ART-based hierarchical clustering algorithm is suggested. The time and space complexity of the algorithm is discussed. A 2-D artificial data set is used to illustrate and compare the effectiveness of the proposed algorithm and K-means algorithm.
Design and Realization of Online Face Recognition Model Based on Fuzzy ART Neural Networks

GU Ming,

计算机科学 , 2007,
Abstract: In this paper,Structure and properties of fuzzy ART are described.Choice and match function is presented.Low pass filter,cutting minimum intensity and generating vector histogram are used to extracted face features.Fuzzy ART uses the vector histogram as the original input vector data to recognize face.Simulation experiment shows that maximum online is 81.25% and offline recognition rate is nearly 100% when the fuzzy ART network parameters are selected properly.
True BLAS-3 Performance QRCP using Random Sampling
Jed A. Duersch,Ming Gu
Mathematics , 2015,
Abstract: The dominant contribution to communication complexity in factorizing a matrix using QR with column pivoting is due to column-norm updates that are required to process pivot decisions. We use randomized sampling to approximate this process which dramatically reduces communication in column selection. We also introduce a sample update formula to reduce the cost of sampling trailing matrices. Using our column selection mechanism we observe results that are comparable to those obtained from the QRCP algorithm, but with performance near unpivoted QR. We also demonstrate strong parallel scalability on shared memory multiple core systems using an implementation in Fortran with OpenMP. This work immediately extends to produce low-rank truncated approximations of large matrices. We propose a truncated QR factorization with column pivoting that avoids trailing matrix updates which are used in current implementations of BLAS-3 QR and QRCP. Provided the truncation rank is small, avoiding trailing matrix updates reduces approximation time by nearly half. By using these techniques and employing a variation on Stewart's QLP algorithm, we develop an approximate truncated SVD that runs nearly as fast as truncated QR.
Field Experiments for Wind Loads on a Low-Rise Building with Adjustable Pitch
Peng Huang,Xu Wang,Ming Gu
International Journal of Distributed Sensor Networks , 2012, DOI: 10.1155/2012/451879
Abstract: A wind engineering research field laboratory, which consists of a full-scale low-rise building and two towers, has been constructed by Tongji University near Shanghai Pudong International Airport to study the characteristics of near-ground wind field and wind pressure on low-rise buildings. The full-scale building, whose roof pitch could be adjusted ranging from 0° to 30°, is 10 m in length, 6 m in width and 8 m in eave's height. It is employed to study the wind pressure on the gable roof of low-rise building with different roof pitches. This paper explicitly and concretely discusses the filed facility, data measurement system, data acquisition system, and tap location to provide references for related researchers. Besides, two pieces of time-histories of ten-minute-length wind pressures are analyzed at 0° and 20° roof pitches respectively to compare with those of a wind tunnel test on a rigid model of 1 : 30 scale. The results show that the tendency for the mean and fluctuating wind pressure distributions between the two kinds of tests is nearly similar.
Enzyme-Catalyzed Modifications of Polysaccharides and Poly(ethylene glycol)
H. N. Cheng,Qu-Ming Gu
Polymers , 2012, DOI: 10.3390/polym4021311
Abstract: Polysaccharides are used extensively in various industrial applications, such as food, adhesives, coatings, construction, paper, pharmaceuticals, and personal care. Many polysaccharide structures need to be modified in order to improve their end-use properties; this is mostly done through chemical reactions. In the past 20 years many enzyme-catalyzed modifications have been developed to supplement chemical derivatization methods. Typical reactions include enzymatic oxidation, ester formation, amidation, glycosylation, and molecular weight reduction. These reactions are reviewed in this paper, with emphasis placed on the work done by the authors. The polymers covered in this review include cellulosic derivatives, starch, guar, pectin, and poly(ethylene glycol).
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