Slow Feature Analysis
Pattern Recognition with Slow Feature Analysis
... Slow feature analysis (SFA) is a new unsupervised algorithm to learn nonlinear functions that extract slowly varying signals from time series (Wiskott and Sejnowski, ...the feature space ...
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Blind Separation of Nonlinear Mixing Signals Using Kernel with Slow Feature Analysis
... kernel- feature spaces separation technique (KTDS EP) and the principle of the slow feature analysis (S ...dimensional feature space using kernel -based ...the slow ...
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How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis
... Perception plays a crucial role in the interaction of animals or humans with their environ- ment. Although processing of sensory information appears to be done straightforwardly by the nervous system, it is a complex ...
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How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis
... Supervised learning from high-dimensional data, for example, multimedia data, is a challenging task. We propose an extension of slow feature analysis (SFA) for supervised dimensionality reduc- tion ...
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Fault classification in dynamic processes using multiclass relevance vector machine and slow feature analysis
... with slow feature analysis fault classification for industrial ...complexity, slow feature analysis is used to extract the inner dynamic features and reduce the ...
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An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
... In this article, we have extended previous theoretical results on SFA to the case where the input data are generated from a set of statistically independent sources. The theory shows that (a) the optimal output of SFA ...
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An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
... One approach is to exploit the temporal structure of the sources (e.g., Harmeling et al., 2003; Blaschke et al., 2007). Blaschke et al. (2007) have proposed to use the tendency of nonlinearly distorted versions of the ...
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Understanding Slow Feature Analysis: A Mathematical Framework
... One approach for the unsupervised learning of such invariant representations is based on the exploitation of temporal correlations in the training data. The basic idea is that representations that are invariant with ...
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Slow feature analysis yields a rich repertoire of complex cell properties
... e.g. the objects we see around us, changes usually on a relatively slow time scale. Sensory signals on the other hand, such as the responses of single receptors in the retina, have a faster time scale, because ...
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Nonstationary time series prediction combined with slow feature analysis
... reached 0.61 for the stationary model but 0.91 for the forcing model. At the eighth prediction step, the correlation coeffi- cients were reduced to 0.39 for the stationary model, but still maintained at 0.45 for the ...
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Slow Delphi: An investigation into information behaviour and the Slow Movement
... between Slow principles and information practices has been limited, and this paper reports a part of the first systematic examination of the ...of Slow Reading, a contemplative and purposeful approach to ...
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Improving classification performance of microarray analysis by feature selection and feature extraction methods
... In this study, we use the classification technique to measure and compare the difference between different feature extraction/ selection methods. Any classification method uses a set of parameters to characterize ...
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Slow Conferencing
... The international conference comes at a cost in terms of our carbon footprint, but it also comes at a cost in terms of building broad communities of interest - particularly for those located in far flung parts of the ...
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Slow & steady
... In her essay entitled Ecopolitics/Ecopoetry, Eleanor Heartney discusses Helen and Newton Harrison’s artistic approaches to environmental problems. In her introductory section of the essay, Heartney writes, “the artist's ...
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Analysis of Slow Read DoS Attack and Countermeasures on Web servers
... our analysis, we found that there is the limitation of effectiveness of attack by a single attacker, and it is determined by the setup of Timeout parameter in Web ...of Slow Read DoS Attack to the Web ...
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Feature Optimization of Whitefly Detection Algorithm using Image Segmentation and Feature Analysis
... optimal feature set is still a topic of active ...reduced feature set is often significantly better than using a full feature ...perfect feature set is continually progressing. Reducing the ...
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Multiscale analysis of slow-fast neuronal learning models with noise
... regime α = 1 seems to be the only one for which the limit cannot be obtained by combining classical averaging principles. Therefore, the present article is focused on this case, in which the averaged system depends ...
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Social Resilience in Aegean Slow Cities: Slow City Seferihisar
... Cittaslow has a charter with 59 different aspects grouped into six different topics including environmental consciousness, support for local products, urban design and infrastructure, technologies and facilities for ...
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A Novel Feature Reduction Method in Sentiment Analysis
... Sentiment analysis applications can be extracted from roughly every possible area such as services, financial services, political elections and customer products ...sentiment analysis, whereby a review is ...
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Analysis Slow Particle Emitted 24Mg with Emulsion Interactions at Relativistic Energies
... of slow and fast protons produced in nucleus- nucleus interactions that no significant differences are observed regarding the mechanism of their production with ...
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