A type of artificial NN that is trained using unsupervised learning to produce a low-dimensional (typically two dimensional), discretized representation of the input space of the training samples, called a map.
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Based on the principle of one-against-one support vector machines (SVMs) multi-class classification algorithm, this paper proposes an extended SVMs method which couples adaptive resonance theory (ART) network to reconstruct ... |
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A modified adaptive resonance theory (mART) neural network of modular structure is proposed. The similarity function and weight resolution of the ART neural networks are modified, and the cluster merging algorithm and ... |
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The World Wide Web has become an important medium for disseminating scientific publications. Many publications are now made available over the Web. However, existing search engines are ineffective in searching these ... |
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This paper presents a new approach for integrating case-based reasoning (CBR) with an ART-Kohonen neural network (ART-KNN) to enhance fault diagnosis. When solving a new problem, the neural network is used to make hypotheses ... |
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Benthic macroinvertebrate communities in stream ecosystems were assessed hierarchically through two-level classification methods of unsupervised learning. Two artificial neural networks were implemented in combination. ... |
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Segmentation is a fundamental step in image description or classification. In recent years, several computational models have been used to implement segmentation methods but without establishing a single analytic solution. ... |
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We propose a new competitive-learning neural network model for colour image segmentation. The model, which is based on the adaptive resonance theory (ART) of Carpenter and Grossberg and on the self-organizing map (SOM) of ... |
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Purpose - We describe an intelligent video categorization engine (IVCE) that uses the learning capability of artificial neural networks (ANNs) to classify suitably preprocessed video segments into a predefined number of ... |
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With the growing rate of network attacks, intelligent methods for detecting new attacks have attracted increasing interest. The RT-UNNID system, introduced in this paper, is one such system, capable of intelligent real-time ... |
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In order to overcome some unavoidable factors, like shift of the part, that influence the crisp neural networks recognition, the present study is dedicated in developing a novel fuzzy neural network (FNN), which integrates ... |
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Photometric clustering of regenerated plants of gladiolus was described using fuzzy adaptive resonance theory (ART) and the resultant grouping pattern was compared with ART 2, and self-organizing map (SOM) neural network ... |
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In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental online learning. This is motivated in the ... |
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In this paper, a new neural network (NN) for fault diagnosis of rotating machinery which synthesizes the theory of adaptive resonance theory (ART) and the learning strategy of Kohonen neural network (KNN), is proposed. For ... |
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We present a mixed-mode VLSI chip performing unsupervised clustering and classification, implementing models of fuzzy adaptive resonance theory (ART) and learning vector quantization (LVQ), and extending to variants such as ... |
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Self-organized maps (SOM) have been applied to analyze the similarities of chemical compounds and to select from a given pool of descriptors the smallest and more relevant subset needed to build robust QSAR models based on ... |
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Motivation: It is well understood that the successful clustering of expression profiles give beneficial ideas to understand the functions of uncharacterized genes. In order to realize such a successful clustering, we ... |
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This article describes a self-organizing neural network architecture that transforms optic flow and eye position information into representations of heading, scene depth, and moving object locations. These representations ... |
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The WSOM (wavelet self-organizing map) model, a neural network for the creation of wavelet bases adapted to the distribution of input data, is introduced. The model provides an efficient online method to construct ... |
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This paper introduces CSOM, a continuous version of the Self-Organizing Map (SOM). The CSOM network generates maps similar to those created with the original SOM algorithm but, due to the continuous nature of the mapping, ... |
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This paper introduces CSOM, a continuous version of the Self-Organizing Map (SOM). The CSOM network generates maps similar to those created with the original SOM algorithm but, due to the continuous nature of the mapping, ... |
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The Self-Organizing ARTMAP Rule Discovery (SOARD) system derives relationships among recognition classes during online learning. SOARD training on input/output pairs produces direct recognition of individual class labels for ... |
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