Self-Organizing Incremental Neural Network (SOINN)Relaxation data representationIn this paper, we propose an unsupervised incremental learning neural network based on local distribution learning, which is called Local Distribution Self-Organizing Incremental Neural Network (LD-SOINN). The LD-SOINN combines ...
This paper describes an incremental unsupervised clustering mechanism for sequence patterns arising from human gestures. Although self-organizing incremental neural network (SOINN) is known as a powerful tool for incremental unsupervised clustering, it is only applicable to static and fixed-length patterns...
The sampling distribution is learned through a local reconstruction-based self-organizing incremental neural network and allows to generate samples from the learned latent distribution. Besides, our method can adapt well to environmental non-vigorous changes and adjust the learned distribution quickly. The...
Self-Organizing Neural Networks for Supervised and Unsupervised Learning and Prediction A neural network architecture for fast, stable, incremental learning of recognition categories and multidimensional maps is described. The architecture, called fuzzy ARTMAP, achieves a synthesis of fuzzy logic and Adaptive...
The sampling distribution is learned through a local reconstruction-based self-organizing incremental neural network and allows to generate samples from the learned latent distribution. Besides, our method can adapt well to environmental non-vigorous changes and adjust the learned distribution quickly. The...
A Sudo,A Satou,O Hasegawa - 《Brain & Neural Networks》 被引量: 1发表: 2008年 A Multidirectional Associative Memory Based on Self-organizing Incremental Neural Network A multidirectional associative memory (AM) is proposed. It is constructed with three layer networks: an input layer, a memory ...
An incremental-learning neural network for the classification of remote-sensing images A novel classifier for the analysis of remote-sensing images is proposed. Such a classifier is based on Radial Basis Function (RBF) neural networks and rel... L.Bruzzone,D.Fernandez Prieto - 《Pattern Recognitio...
Self-organizing incremental neural network (SOINN) [12] and its enhanced version (ESOINN) [13] are also based on an incremental structure where the first version is using a two layers network while the enhanced version proposed a single layer network. These proposals, however, do not guarantee...
The batch training algorithm is generally much faster than the incremental algorithm, and it is the default algorithm for SOFM training. You can experiment with this algorithm on a simple data set with the following commands: x = simplecluster_dataset net = selforgmap([6 6]); net = train(...
Nonparametric Density Estimation Based on Self-Organizing Incremental Neural Network for Large Noisy Data With the ongoing development and expansion of communication networks and sensors, massive amounts of data are continuously generated in real time from real... Y Nakamura,O Hasegawa - 《IEEE Transac...