In this article, two clustering techniques based on neural networks are introduced. The two neural network models are the Harmony theory network (HTN) and the self-organizing logic neural network (SOLNN), both of which are characterized by parallel processing, a distributed architecture, and a large
Activation clustering in neural and social networks
β Scribed by Marko Puljic; Robert Kozma
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 153 KB
- Volume
- 10
- Category
- Article
- ISSN
- 1076-2787
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β¦ Synopsis
Abstract
Questions related to the evolution of the structure of networks have received recently a lot of attention in the literature. But what is the state of the network given its structure? For example, there is the question of how the structures of neural networks make them behave? Or, in the case of a network of humans, the question could be related to the states of humans in general, given the structure of the social network. The models based on stochastic processes developed in this article, do not attempt to capture the fine details of social or neural dynamics. Rather they aim to describe the general relationship between the variables describing the network and the aggregate behavior of the network. A number of nontrivial results are obtained using computer simulations. Β© 2005 Wiley Periodicals, Inc. Complexity 10: 42β50, 2005
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