Growing self-organizing networks - Why ?
نویسنده
چکیده
The reasons to use growing self-organizing networks are investigated. First an overview of several models of this kind is given are they are related to other approaches. Then two examples are presented to illustrate the speci c properties and advantages of incremental networks. In each case a non-incremental model is used for comparison purposes. The rst example is pattern classi cation and compares the supervised growing neural gas model to a conventional radial basis function approach. The second example is data visualization and contrasts the growing grid model and the self-organizing feature map.
منابع مشابه
Growing Neural Networks using Soft Competitive Learning
This paper gives an overview of some classical Growing Neural Networks (GNN) using soft competitive learning. In soft competitive learning each input signal is characterized by adapting in addition to the winner also some other neurons of the network. The GNN is also called the ANN with incremental learning. The artificial neural networks (ANN) mapping capability depends on the number of layers...
متن کاملA Multi-signal Variant for the GPU-based Parallelization of Growing Self-Organizing Networks
Among the many possible approaches for the parallelization of self-organizing networks, and in particular of growing self-organizing networks, perhaps the most common one is producing an optimized, parallel implementation of the standard sequential algorithms reported in the literature. In this paper we explore an alternative approach, based on a new algorithm variant specifically designed to m...
متن کاملTowards Growing Self-Organizing Neural Networks with Fixed Dimensionality
The competitive learning is an adaptive process in which the neurons in a neural network gradually become sensitive to different input pattern clusters. The basic idea behind the Kohonen’s Self-Organizing Feature Maps (SOFM) is competitive learning. SOFM can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main features of this kind of mappi...
متن کاملEarly lexical development in a self-organizing neural network
In this paper we present a self-organizing neural network model of early lexical development called DevLex. The network consists of two self-organizing maps (a growing semantic map and a growing phonological map) that are connected via associative links trained by Hebbian learning. The model captures a number of important phenomena that occur in early lexical acquisition by children, as it allo...
متن کاملApplication of growing self-organizing map to small-world networking
This paper studies a novel application of growing self-organizing maps to networking. In our algorithm nodes for the networking are applied successively as input data. Adapting to the input, the map can grow and can change the topology. Performing basic numerical experiments, we have confirmed that our algorithm can generate small-world like networks characterized by relatively small average pa...
متن کامل