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Efficient Layer-Wise N:M Sparse CNN Accelerator with Flexible SPEC: Sparse Processing Element Clusters [PDF]
Micromachines, 2023 Recently, the layer-wise N:M fine-grained sparse neural network algorithm (i.e., every M-weights contains N non-zero values) has attracted tremendous attention, as it can effectively reduce the computational complexity with negligible accuracy loss ...
Xiaoru Xie +3 more
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A Survey of Sparse Representation: Algorithms and Applications
IEEE Access, 2015 Sparse representation has attracted much attention from researchers in fields of signal processing, image processing, computer vision, and pattern recognition.
Zheng Zhang +4 more
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IEEE Access, 2018 In the past decade, sparse and low-rank recovery has drawn much attention in many areas such as signal/image processing, statistics, bioinformatics, and machine learning.
Fei Wen +3 more
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Smooth Polynomial Approach for Microwave Imaging in Sparse Processing Framework
IEEE Access, 2022 We developed a novel qualitative imaging algorithm based on a polynomial approximation of the unknown contrast and sparse ( $l_{1}$ ) regularization.
Tushar Singh +3 more
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IET Radar, Sonar & Navigation, 2022 Digital‐to‐analogue and analogue‐to‐digital in a digital array radar limits the transmission and reception of instantaneous broadband signals (IBSs), which makes it a technical bottleneck for digital array radar to obtain an instantaneous broadband high ...
Hao Wang +3 more
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MOSDA: On-Chip Memory Optimized Sparse Deep Neural Network Accelerator With Efficient Index Matching
IEEE Open Journal of Circuits and Systems, 2021 The irregular data access pattern caused by sparsity brings great challenges to efficient processing accelerators. Focusing on the index-matching property in DNN, this article aims to decompose sparse DNN processing into easy-to-handle processing tasks ...
Hongjie Xu +2 more
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Research on software credibility algorithm based on deep convolutional sparse coding [PDF]
MATEC Web of Conferences, 2021 Based on the author's research time, this paper studies the software credibility algorithm based on deep convolutional sparse coding. Firstly, it summarizes the convolutional sparse coding and trust classification system, and then constructs the ...
Xu Zhaosheng
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Measuring Product Similarity with Hesitant Fuzzy Set for Recommendation
Mathematics, 2021 The processing of a sparse matrix is a hot topic in the recommendation system. This paper applies the method of hesitant fuzzy set to study the sparse matrix processing problem.
Chunsheng Cui, Jielu Li, Zhenchun Zang
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Sparse-PE: A Performance-Efficient Processing Engine Core for Sparse Convolutional Neural Networks
IEEE Access, 2021 Sparse convolutional neural network (CNN) models reduce the massive compute and memory bandwidth requirements inherently present in dense CNNs without a significant loss in accuracy. Sparse CNNs, however, present their own set of challenges including non-
Mahmood Azhar Qureshi, Arslan Munir
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Current Developments of Sparse Microwave Imaging
Leida xuebao, 2014 The sparse microwave imaging combines the sparse signal processing theory with radar imaging to obtain new theory, new system, and new methodology of microwave imaging.
Wu Yi-rong +5 more
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