نتایج جستجو برای: decomposing intensity matrix
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Unlike the method without pivoting, Gaussian elimination with partial pivoting consecutively applies row permutation to matrix A in order to avoid possible akk diagonal entries of matrix A being equal to zero. Gaussian elimination with partial pivoting solves the matrix equation Ax = b decomposing matrix A into a lower L and upper U triangular matrices such that PA = LU, where P is a row permut...
carbon nanotube (cnt) is considered as a new generation of material possessing superior mechanical, thermal and electrical properties. the applications of cnt, especially in composite materials, i.e. carbon nanotube reinforced polymer have received great attention and interest in recent years. to characterize the influence of cnt on the stress intensity factor of nanocomposites, three fracture ...
In this article, we investigate the Minimum Cardinality Segmentation Problem (MCSP), an NP-hard combinatorial optimization problem arising in intensity-modulated radiation therapy. The problem consists in decomposing a given nonnegative integer matrix into a nonnegative integer linear combination of a minimum cardinality set of binary matrices satisfying the consecutive ones property. We show h...
Aerial image simulation is one of the most critical components in the model-based optical proximity correction (OPC), which has become a necessary part of resolution enhancement techniques used to improve the performance of subwavelength optical lithography. In this paper, a fast aerial image simulation method is proposed for partially coherent systems by decomposing the transmission cross coef...
The network traffic matrix is widely used in network operation and management. It is therefore of crucial importance to analyze the components and the structure of the network traffic matrix, for which several mathematical approaches such as Principal Component Analysis (PCA) were proposed. In this paper, we first argue that PCA performs poorly for analyzing traffic matrix that is polluted by l...
This is an attempt to devise a memory efficient WDR (Wavelet Difference Reduction) algorithm by decomposing a matrix using customized Echelon algorithm and applying WDR on it in parts. The standard process of WDR algorithm requires the entire matrix to be available in RAM (random access memory) which might not be feasible always or for a longer duration till the entire matrix is encoded. This i...
We examine the $\mathcal{H}_2$ norm of matrix-weighted leader-follower consensus on series-parallel networks. By using an extension electrical network theory matrix-valued resistances, voltages and currents, we show that computation can be performed efficiently by decomposing into atomic elements composition rules. Lastly, problem adapting edge weights to optimize network.
Nonnegative matrix factorization (NMF) is the problem of decomposing a given nonnegative n×m matrix M into a product of a nonnegative n × d matrix W and a nonnegative d ×m matrix H. A longstanding open question, posed by Cohen and Rothblum in 1993, is whether a rational matrix M always has an NMF of minimal inner dimension d whose factors W and H are also rational. We answer this question negat...
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