Results 271 to 280 of about 1,582,878 (315)
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A novel method for calculating the convolution sum of two finite length sequences
IEEE Transactions on Education, 1996J. Pierre
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A MONOTONIC CONVOLUTION FOR MINKOWSKI SUMS
International Journal of Computational Geometry & Applications, 2007We present a monotonic convolution for planar regions A and B bounded by line and circular arc segments. The Minkowski sum equals the union of the cells with positive crossing numbers in the arrangement of the convolution, as is the case for the kinetic convolution.
Milenkovic, Victor, Sacks, Elisha
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Partial Sum Quantization for Computing-In-Memory-Based Neural Network Accelerator
IEEE Transactions on Circuits and Systems - II - Express Briefs, 2023Computing-in-memory (CIM) has been successful as an ideal hardware platform to improve the performance and efficiency of convolutional neural networks (CNNs).
Jinyu Bai +4 more
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Shifted convolution sum with weighted average: GL(3)×GL(3) setup
Journal of Number TheoryThis article will prove non-trivial estimates for the average and weighted average version of general $GL(3) \times GL(3)$ shifted convolution sums by using the circle method.
Mohd Harun, Saurabh Kumar Singh
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SIAM Journal on Mathematical Analysis, 1972
Let $\Omega $ be an open set in $R_n $ and let $\mathcal{E}(\Omega )$ denote the space of infinitely differentiable functions on $\Omega $. Necessary and sufficient conditions are exhibited for a family $\{ \Omega _i \} _{i = 1}^N $ of open sets in $R_n$ and a family $\{ S_i \} _{i = 1}^N \subset \mathcal{E}'(R_n )$ in order that the convolution ...
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Let $\Omega $ be an open set in $R_n $ and let $\mathcal{E}(\Omega )$ denote the space of infinitely differentiable functions on $\Omega $. Necessary and sufficient conditions are exhibited for a family $\{ \Omega _i \} _{i = 1}^N $ of open sets in $R_n$ and a family $\{ S_i \} _{i = 1}^N \subset \mathcal{E}'(R_n )$ in order that the convolution ...
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A sharp discrete convolution sum estimate
Communications in Nonlinear Science and Numerical Simulation, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Martin Stynes, Dongling Wang
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Knapsack and Subset Sum with Small Items
International Colloquium on Automata, Languages and Programming, 2021Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various parameters. In
Adam Polak +2 more
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Neighbor Interaction Aware Graph Convolution Networks for Recommendation
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020Personalized recommendation plays an important role in many online services. Substantial research has been dedicated to learning embeddings of users and items to predict a user's preference for an item based on the similarity of the representations.
Jianing Sun +7 more
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Evaluation of some convolution sums
AIP Conference Proceedings, 2015We evaluate the convolution sums∑l+50m=nσ(l)σ(m), ∑2l+25m=nσ(l)σ(m), ∑l+25m=nσ(l)σ(m),∑l+m=n,l≡a mod5σ(l)σ(m), for a=0,1,2,3,4using the theory of quasimodular forms.
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Sum-product decoding of convolutional codes
2009 Fourth International Workshop on Signal Design and its Applications in Communications, 2009This article proposes two methods to improve the sum-product soft-in/soft-out decoding performance of convolutional codes. The first method is to transform a parity check equation in such a way as to remove cycles of length four in a Tanner graph of a convolutional code, and performs sum-product algorithm (SPA) with the transformed parity check ...
Toshiyuki Shohon +2 more
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