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Sardar Anisul Haque, Mohammad Tanvir Parvez and Shahadat Hossain
Matrix?matrix multiplication is of singular importance in linear algebra operations with a multitude of applications in scientific and engineering computing. Data structures for storing matrix elements are designed to minimize overhead information as wel...
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Ivan Volaric and Victor Sucic
One of the frequently used classes of sparse reconstruction algorithms is based on the iterative shrinkage/thresholding procedure, in which the thresholding parameter controls a trade-off between the algorithm?s accuracy and execution time. In order to a...
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Qing Li, Decheng Zuo, Yi Feng and Dongxin Wen
Backpack computers require powerful, intelligent computing capabilities for field wearables while taking energy consumption into careful consideration. A recommended solution for this demand is the CPU + NPU-based SoC. In many wearable intelligence appli...
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Xiaoyi Fu, Lei Liang, Wenlai Ma, Hutao Cui and Yang Zhao
Designing spacecraft involves a careful equilibrium to avoid overengineering or underdesigning, which underscores the importance of employing thermal uncertainty analysis. A key part of this analysis is modeling thermal conditions, but this is often a co...
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Beimbet Daribayev, Aksultan Mukhanbet and Timur Imankulov
The Poisson equation is a fundamental equation of mathematical physics that describes the potential distribution in static fields. Solving the Poisson equation on a grid is computationally intensive and can be challenging for large grids. In recent years...
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Yang Wang, Jie Liu, Xiaoxiong Zhu, Qingyang Zhang, Shengguo Li and Qinglin Wang
Structured grid-based sparse matrix-vector multiplication and Gauss?Seidel iterations are very important kernel functions in scientific and engineering computations, both of which are memory intensive and bandwidth-limited. GPDSP is a general purpose dig...
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Xiaoyi Fu, Yuntao Hua, Wenlai Ma, Hutao Cui and Yang Zhao
Thermal uncertainty analysis of spacecraft is an important method to avoid overdesign and underdesign problems. In the context of uncertainty analysis, thermal models representing multiple operating conditions must be invoked repeatedly, leading to subst...
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Weidong Wang, Xiangshui Li, Kai Zhang, Juan Shi, Wentao Shi and Wasiq Ali
To minimize the major decline in direction of arrival (DOA) estimation performance for an acoustic vector sensor array (AVSA) with the coexistence of axial deviation and non-uniform noise, a two-step iterative minimization (TSIM) method is proposed in th...
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Jialu Sui and Jian Yin
Nowadays, as the number of items is increasing and the number of items that users have access to is limited, user-item preference matrices in recommendation systems are always sparse. This leads to a data sparsity problem. The latent factor analysis (LFA...
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Rasoul Shafipour and Gonzalo Mateos
We develop online graph learning algorithms from streaming network data. Our goal is to track the (possibly) time-varying network topology, and affect memory and computational savings by processing the data on-the-fly as they are acquired. The setup enta...
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