منابع مشابه
Self-Organizing Feature Maps with Self-Organizing Neighborhood Widths
Self-organizing feature maps with self-determined local neighborhood widths are applied to construct principal manifolds of data distributions. This task exempli es the problem of the learning of learning parameters in neural networks. The proposed algorithm is based upon analytical results on phase transitions in self-organizing feature maps available for idealized situations. By illustrative ...
متن کاملSpatio-Temporal Self-Organizing Feature Maps
Thus far, the success of capturing and classifying temporal information with neural networks has been limited. Our methodology adds a spatio-temporal coupling to the Self-Organized Feature Map (SOFM) which creates temporally and spatially localized neighborhoods in the map. The spatio-temporal coupling is based on traveling waves of activity starting at each winning node which are naturally att...
متن کاملUnsupervised Feature Learning using Self-organizing Maps
In recent years a great amount of research has focused on algorithms that learn features from unlabeled data. In this work we propose a model based on the Self-Organizing Map (SOM) neural network to learn features useful for the problem of automatic natural images classification. In particular we use the SOM model to learn single-layer features from the extremely challenging CIFAR-10 dataset, c...
متن کاملSelf-organizing feature maps predicting sea levels
In this paper, a new method for predicting sea levels employing self-organizing feature maps is introduced. For that purpose the maps are transformed from an unsupervised learning procedure to a supervised one. Two concepts, originally developed to solve the problems of convergence of other network types, are proposed to be applied to Kohonen networks: a functional relationship between the numb...
متن کاملEmergence in Self Organizing Feature Maps
This paper sheds some light on the claim that Emergent SOM (ESOM) are different from other SOM. The discussion in philosophy and epistemology about Emergence is summarized in the form of postulates. The properties of SOM are compared to these postulates. SOM fulfill most of the postulates. The most critical of the postulates are those concerned with “the whole is more than the sum of its parts”...
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ژورنال
عنوان ژورنال: Transactions on Machine Learning and Artificial Intelligence
سال: 2018
ISSN: 2054-7390
DOI: 10.14738/tmlai.46.2533