Results 21 to 30 of about 502,069 (324)
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
doaj +1 more source
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
Realization of Spatial Sparseness by Deep ReLU Nets With Massive Data [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2019 The great success of deep learning poses urgent challenges for understanding its working mechanism and rationality. The depth, structure, and massive size of the data are recognized to be three key ingredients for deep learning.
C. Chui +3 more
semanticscholar +1 more source
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
doaj +1 more source
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
doaj +1 more source
Factors of Sparse Polynomials are Sparse
CoRR, 2014 This paper was removed due to an error in the proof (Claim 4.12 as stated is not true)
Dvir, Zeev, de Oliveira, Rafael Mendes
openaire +4 more sources
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
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
doaj +1 more source
Block-wise Dynamic Sparseness [PDF]
, 2020 Neural networks have achieved state of the art performance across a wide variety of machine learning tasks, often with large and computation-heavy models.
Hadifar, Amir +7 more
core +1 more source