Results 21 to 30 of about 864,269 (299)
Explicit Object Representation by Sparse Neural Codes [PDF]
, 2008 Neurons have been identified in the human medial temporal lobe (MTL) that display a strong selectivity for only a few stimuli (such as familiar individuals or landmark buildings) out of perhaps 100 presented to the test subject.
Waydo, Stephen J.
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Large-Scale Visualization of Sparse Matrices [PDF]
, 2014 An efficient algorithm for parallel acquisition of visualization data for large sparse matrices is presented and evaluated both analytically and empirically.
Tvrdik, P. +3 more
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Learning from sparse codes [PDF]
, 2016 In this paper we address the problem of learning image structures directly from sparse codes. We first model images as linear combinations of molecules, which are themselves groups of atoms from a redundant dictionary.
Karygianni, Sofia +3 more
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Voxel selection in fMRI data analysis based on sparse representation [PDF]
, 2009 Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI)
Namburi, Praneeth +5 more
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Sparse Spectrotemporal Coding of Sounds [PDF]
EURASIP Journal on Advances in Signal Processing, 2003 Summary: Recent studies of biological auditory processing have revealed that sophisticated spectrotemporal analyses are performed by central auditory systems of various animals. The analysis is typically well matched with the statistics of relevant natural sounds, suggesting that it produces an optimal representation of the animal's acoustic biotope ...
David J. Klein +2 more
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IET Communications, 2023 This paper studies the blind recognition method of the sparse parity‐check matrices of low‐density parity‐check codes in noncooperative communication, which is critical to the reverse analysis of communication protocols using LDPC codes.
Yong Ding, Zhiping Huang, Jing Zhou
doaj +1 more source
Semi-supervised sparse coding [PDF]
2014 International Joint Conference on Neural Networks (IJCNN), 2014 Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled.
Jim Jing-Yan Wang, Xin Gao 0001
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Measurement-induced phase transitions in sparse nonlocal scramblers
Physical Review Research, 2022 Measurement-induced phase transitions arise due to a competition between the scrambling of quantum information in a many-body system and local measurements.
Tomohiro Hashizume +2 more
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Fast Convolutional Sparse Coding [PDF]
2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013 Sparse coding has become an increasingly popular method in learning and vision for a variety of classification, reconstruction and coding tasks. The canonical approach intrinsically assumes independence between observations during learning. For many natural signals however, sparse coding is applied to sub-elements ( i.e.
Hilton Bristow +2 more
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Reconfigurable rateless codes [PDF]
, 2009 We propose novel reconfigurable rateless codes, that are capable of not only varying the block length but also adaptively modify their encoding strategy by incrementally adjusting their degree distribution according to the prevalent channel conditions ...
Chen, Sheng +3 more
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