منابع مشابه
Topographic Independent Component Analysis
In ordinary independent component analysis, the components are assumed to be completely independent, and they do not necessarily have any meaningful order relationships. In practice, however, the estimated "independent" components are often not at all independent. We propose that this residual dependence structure could be used to define a topographic order for the components. In particular, a ...
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Topographic and overcomplete representations of natural images/videos are important problems in computational neuroscience. We propose a new method using both topographic and overcomplete representations of natural images, showing emergence of properties similar to those of complex cells in primary visual cortex (V1). This method can be considered as an extension of model in Hyvärinen et al. [T...
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Data-driven fMRI analysis techniques include independent component analysis (ICA) and different types of clustering in the temporal domain. Since each of these methods has its particular strengths, it is natural to look for an approach that unifies Kohonen's self-organizing map and ICA. This is given by the topographic independent component analysis. While achieved by a slight modification of t...
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Topographic independent component analysis (TICA) is an interesting extension of the conventional ICA, which aims at finding a linear decomposition into approximately independent components with the dependence between two components is approximated by their proximity in the topographic representation. In this paper we apply the topographic ICA to gene expression time series data and compare it ...
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Understanding the underlying mechanisms that drive human visual attention is a topic of immense interest. Most of the work is focused on extracting manually selected features that might resemble the human visual processing pathway and using a combination of those features to train a classifier that learns to predict where humans look. In contrast, we will learn the features in an unsupervised w...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2001
ISSN: 0899-7667,1530-888X
DOI: 10.1162/089976601750264992