Results 11 to 20 of about 68 (62)
Generalized discriminant orthogonal nonnegative tensor factorization for facial expression recognition. [PDF]
ScientificWorldJournal, 2014 In order to overcome the limitation of traditional nonnegative factorization algorithms, the paper presents a generalized discriminant orthogonal non‐negative tensor factorization algorithm. At first, the algorithm takes the orthogonal constraint into account to ensure the nonnegativity of the low‐dimensional features.
XiuJun Z, Chang L.
europepmc +2 more sources
Advances in nonnegative matrix and tensor factorization. [PDF]
Comput Intell Neurosci, 2008 Computational Intelligence and Neuroscience, Volume 2008, Issue 1, 2008.
Cichocki A +4 more
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Single-trial decoding of bistable perception based on sparse nonnegative tensor decomposition. [PDF]
Comput Intell Neurosci, 2008 The study of the neuronal correlates of the spontaneous alternation in perception elicited by bistable visual stimuli is promising for understanding the mechanism of neural information processing and the neural basis of visual perception and perceptual decision‐making.
Wang Z, Maier A, Logothetis NK, Liang H.
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Probabilistic latent variable models as nonnegative factorizations. [PDF]
Comput Intell Neurosci, 2008 This paper presents a family of probabilistic latent variable models that can be used for analysis of nonnegative data. We show that there are strong ties between nonnegative matrix factorization and this family, and provide some straightforward extensions which can help in dealing with shift invariances, higher‐order decompositions and sparsity ...
Shashanka M, Raj B, Smaragdis P.
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Brain connectivity analysis: a short survey. [PDF]
Comput Intell Neurosci, 2012 This short survey the reviews recent literature on brain connectivity studies. It encompasses all forms of static and dynamic connectivity whether anatomical, functional, or effective. The last decade has seen an ever increasing number of studies devoted to deduce functional or effective connectivity, mostly from functional neuroimaging experiments ...
Lang EW +4 more
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Estimating Network Flow Length Distributions via Bayesian Nonnegative Tensor Factorization
Wireless Communications and Mobile Computing, Volume 2019, Issue 1, 2019., 2019 In this paper, we develop a framework to estimate network flow length distributions in terms of the number of packets. We model the network flow length data as a three‐way array with day‐of‐week, hour‐of‐day, and flow length as entities where we observe a count.
Barış Kurt +4 more
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Why You Go Reveals Who You Know: Disclosing Social Relationship by Cooccurrence
Wireless Communications and Mobile Computing, Volume 2017, Issue 1, 2017., 2017 The popularity of location‐based services (LBS) and the ubiquity of sensor device have resulted in rich spatiotemporal data. A large number of human behaviors had been recorded including cooccurrence which refers to the phenomenon that two people have been to the same places at the same time.
Feng Yi +4 more
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Science and Technology of Nuclear Installations, Volume 2017, Issue 1, 2017., 2017 We present an overview of fission chamber’s functioning modes, theoretical aspects of the nonnegative matrix factorization methods, and the opportunities that offer neutron data processing in order to achieve neutron flux monitoring tasks. Indeed, it is a part of research project that aimed at applying Blind Source Separation methods for in‐core and ex‐
Hanane Arahmane +3 more
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IET Signal Processing, Volume 9, Issue 8, Page 587-595, October 2015., 2015 In this paper, the authors address the tasks of audio source counting and separation for two‐channel instantaneous mixtures. This goal is achieved in two steps. First, a novel scheme is proposed for estimating the number of sources and the corresponding channel intensity difference (CID) values.
Sayeh Mirzaei +2 more
wiley +1 more source
Mathematical Problems in Engineering, Volume 2014, Issue 1, 2014., 2014 A novel facial expression recognition algorithm based on discriminant neighborhood preserving nonnegative tensor factorization (DNPNTF) and extreme learning machine (ELM) is proposed. A discriminant constraint is adopted according to the manifold learning and graph embedding theory. The constraint is useful to exploit the spatial neighborhood structure
Gaoyun An +5 more
wiley +1 more source