Results 21 to 30 of about 489,349 (320)
Drones, 2023 In this paper, we address the challenge of low recognition rates in existing methods for radar signals from unmanned aerial vehicles (UAV) with low signal-to-noise ratios (SNRs).
Xuemin Liu +5 more
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Sparse Recovery Using Sparse Matrices [PDF]
Proceedings of the IEEE, 2010 In this paper, we survey algorithms for sparse recovery problems that are based on sparse random matrices. Such matrices has several attractive properties: they support algorithms with low computational complexity, and make it easy to perform incremental updates to signals.
Gilbert, Anna, Indyk, Piotr
openaire +4 more sources
Lifelong Learning Augmented Short Text Stream Clustering Method
IEEE Access, 2021 Depending on the scanning mode, existing short text stream clustering methods can be divided into the following two kinds of methods: one-pass-based and batch-based.
Jipeng Qiang +4 more
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Sensors, 2021 In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle
Yehao Ma +5 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Anomaly target detection has been a hotspot of the hyperspectral imagery (HSI) processing in recent decades. One of the key research points in the HSI anomaly detection is the accurate descriptions of the background and anomaly targets.
Yan Zhang +6 more
doaj +1 more source
Research on compressive sensing of strong earthquake signals for earthquake early warning
Geomatics, Natural Hazards & Risk, 2021 Earthquake early warning is an effective method to reduce casualties and losses. Based on the theory of compressive sensing, this paper proposes a strong earthquake signal processing architecture based on compressive sensing for difficulties of the ...
Jiening Xia +4 more
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Sparseness and expansion in sensory representations. [PDF]
Neuron, 2014 SummaryIn several sensory pathways, input stimuli project to sparsely active downstream populations that have more neurons than incoming axons. Here, we address the computational benefits of expansion and sparseness for clustered inputs, where different ...
B. Babadi, H. Sompolinsky
semanticscholar +2 more sources
The Contingent Effects of Social Network Sparseness and Centrality on Managerial Innovativeness
Journal of Management Studies, 2014 Wai Fong Boh, Sze Sze Wong
exaly +2 more sources
The Relationship between Sparseness and Energy Consumption of Neural Networks
Journal of Neural Transplantation and Plasticity, 2020 About 50-80% of total energy is consumed by signaling in neural networks. A neural network consumes much energy if there are many active neurons in the network. If there are few active neurons in a neural network, the network consumes very little energy.
Guanzheng Wang +3 more
semanticscholar +1 more source
Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video [PDF]
Computer Vision and Pattern Recognition, 2015 This paper addresses the challenge of 3D full-body human pose estimation from a monocular image sequence. Here, two cases are considered: (i) the image locations of the human joints are provided and (ii) the image locations of joints are unknown.
Xiaowei Zhou +4 more
semanticscholar +1 more source