Results 31 to 40 of about 20,444,531 (305)
DOA Estimation in Partially Correlated Noise Using Low-Rank/Sparse Matrix Decomposition [PDF]
, 2014 We consider the problem of direction-of-arrival (DOA) estimation in unknown partially correlated noise environments where the noise covariance matrix is sparse. A sparse noise covariance matrix is a common model for a sparse array of sensors consisted of
Babaie-Zadeh, Massoud +4 more
core +1 more source
Spatially Sparse Precoding in Millimeter Wave MIMO Systems [PDF]
IEEE Transactions on Wireless Communications, 2013 Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications and all cellular systems.
Omar El Ayach +4 more
semanticscholar +1 more source
Compute Less to Get More: Using ORC to Improve Sparse Filtering [PDF]
, 2015 Sparse Filtering is a popular feature learning algorithm for image classification pipelines. In this paper, we connect the performance of Sparse Filtering with spectral properties of the corresponding feature matrices.
Guadarrama, Sergio, Lederer, Johannes
core +1 more source
Remote Sensing, 2021 In this paper we consider the tracking problem of a moving target competing against noise and clutter in a surveillance radar scenario. For a single array-antenna multiple-target tracking system and according to the Track-Before-Detect paradigm, we ...
Nicomino Fiscante +5 more
doaj +1 more source
Comparative Analysis of Sparse Matrix Algorithms For Information Retrieval [PDF]
Journal of Systemics, Cybernetics and Informatics, 2003 We evaluate and compare the storage efficiency of different sparse matrix storage formats as index structure for text collection and their corresponding sparse matrixvector multiplication algorithm to perform query processing in information retrieval (IR)
Nazli Goharian, Ankit Jain, Qian Sun
doaj
Sparse Deconvolution Using Support Vector Machines
EURASIP Journal on Advances in Signal Processing, 2008 Sparse deconvolution is a classical subject in digital signal processing, having many practical applications. Support vector machine (SVM) algorithms show a series of characteristics, such as sparse solutions and implicit regularization, which make them ...
Aníbal R. Figueiras-Vidal +5 more
doaj +1 more source
A novel sparse representation algorithm for AIS real-time signals
EURASIP Journal on Wireless Communications and Networking, 2018 Sparse representation of signals based on a redundant dictionary is a new signal representation theory. Recent research activities in this field have concentrated mainly on the study of dictionary design and sparse decomposition algorithms.
Shuaiheng Huai, Shufang Zhang
doaj +1 more source
3D SAR Imaging Method Based on Learned Sparse Prior
Leida xuebao, 2023 The development of 3D Synthetic Aperture Radar (SAR) imaging is currently hampered by issues such as high data dimension, high system complexity, and low imaging processing efficiency.
Mou WANG +5 more
doaj +1 more source
PCGen: A Fully Parallelizable Point Cloud Generative Model
SensorsGenerative models have the potential to revolutionize 3D extended reality. A primary obstacle is that augmented and virtual reality need real-time computing.
Nicolas Vercheval +3 more
doaj +1 more source
International Journal of Distributed Sensor Networks, 2020 Sparse decomposition has excellent adaptability and high flexibility in describing arbitrary complex signals based on redundant and over-complete dictionary, thus having the advantage of being free from the limitations of traditional signal processing ...
Hongchao Wang, Wenliao Du
doaj +1 more source