Results 31 to 40 of about 522,381 (263)
Shock and Vibration, 2020 The feature extraction of wheelset-bearing fault is important for the safety service of high-speed train. In recent years, sparse representation is gradually applied to the fault diagnosis of wheelset-bearing.
Zhan Xing +3 more
doaj +1 more source
Robust Sparse Representation for Incomplete and Noisy Data
Information, 2015 Owing to the robustness of large sparse corruptions and the discrimination of class labels, sparse signal representation has been one of the most advanced techniques in the fields of pattern classification, computer vision, machine learning and so on ...
Jiarong Shi, Xiuyun Zheng, Wei Yang
doaj +1 more source
Compressive Sampling for Remote Control Systems [PDF]
, 2012 In remote control, efficient compression or representation of control signals is essential to send them through rate-limited channels. For this purpose, we propose an approach of sparse control signal representation using the compressive sampling ...
Hayashi, Kazunori +2 more
core +4 more sources
Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse Datasets [PDF]
, 2016 Nonnegative Matrix Factorization (NMF) with Kullback-Leibler Divergence (NMF-KL) is one of the most significant NMF problems and equivalent to Probabilistic Latent Semantic Indexing (PLSI), which has been successfully applied in many applications.
Ho, Tu Bao, Nguyen, Duy Khuong
core +2 more sources
Spatial relationships over sparse representations [PDF]
2009 24th International Conference Image and Vision Computing New Zealand, 2009 New imaging devices provide image data at very high spatial resolution acquisition and throughput rate. In satellite or medical two-dimensional images, high-content and large image issues plead for more high semantic level interactions between the computer vision systems and the end-users in order to leverage the cognitive symbiosis between both ...
Lomenie, Nicolas, Racoceanu, Daniel
openaire +2 more sources
Sparse representation-based synthetic aperture radar imaging [PDF]
, 2011 There is increasing interest in using synthetic aperture radar (SAR) images in automated target recognition and decision-making tasks. The success of such tasks depends on how well the reconstructed SAR images exhibit certain features of the underlying ...
Cetin, Mujdat +3 more
core +1 more source
Discriminative collaborative representation for multimodal image classification
International Journal of Advanced Robotic Systems, 2017 Sparse representation has been widely researched for image-based classification. However, sparse representation classification directly treats training samples as a dictionary, so it needs a large training set and is time consuming, especially for a ...
Dawei Sun +3 more
doaj +1 more source
Identification of Matrices Having a Sparse Representation [PDF]
, 2007 We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary.
Pfander, Goetz E. +2 more
core +5 more sources
Sparse representation of Gravitational Sound [PDF]
Journal of Sound and Vibration, 2018 Gravitational Sound clips produced by the Laser Interferometer Gravitational-Wave Observatory (LIGO) and the Massachusetts Institute of Technology (MIT) are considered within the particular context of data reduction. It is shown that these types of signals can be approximated at high quality using much less elementary components than those required ...
Rebollo Neira, Laura +1 more
openaire +4 more sources
Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle
The Scientific World Journal, 2014 As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently ...
Xiangwei Xing +3 more
doaj +1 more source