Kohonen self-organisation maps are a well know classification tool, commonly used in a wide variety of problems, but with limited applications in time series forecasting context. In this paper, we propose a forecasting method specifically designed for multi-dimensional long-term trends prediction, with a double application of the Kohonen algorithm. Practical applications of the method are also ...

This paper introduces a hierarchical Self-Organizing Feature Map (SOFM). The partial maps consist of individual numbers of neurons, which makes a cluster analysis with di erent degrees of resolution possible. A de nition of a special Mahalanobis space of the data set during the learning improves the properties concerning clusters with low density.

This study examines the potential of a selforganising map for classifying corporate takeover and merger targets using a range of financial information about companies. A sample of 200 US quoted companies, half which were merger or takeover targets and half which were not, are used to train and test the model. The best self-organised map correctly classified 94.8% of the firms in the training se...

In help of the Kohonen’s self-organizing maps we present a topological local principal component analysis model which is capable of exploiting both the global topological structure and each local cluster structure. A newly proposed self-organizing strategy that can enhance the learning speed is introduced to train the model. c © 2003 Elsevier B.V. All rights reserved.

An application of laterally interconnected self-organizing maps (LISSOM) to handwritten digit recognition is presented. The lateral connections learn the correlations of activity between units on the map. The resulting excitatory connections focus the activity into local patches and the inhibitory connections decorrelate redundant activity on the map. The map thus forms internal representations...

The availability of large music collections calls for ways to efficiently access and explore them. We present a new approach which combines descriptors derived from audio analysis with meta-information to create different views of a collection. Such views can have a focus on timbre, rhythm, artist, style or other aspects of music. For each view the pieces of music are organized on a map in such...

An understanding of language processing in humans is critical if realistic computerised systems are to be produced to perform various language operations. The examination of aphasia in individuals has provided a large amount of information on the organisation of language processing, with particular reference to the regions in the brain where processing occurs and the ability to regain language ...

In the real world, it is not always true that the nextdoor house is close to my house, in other words, “neighbors” are not always “true neighbors”. In this study, we propose a new Self-Organizing Map (SOM) algorithm, SOM with False Neighbor degree between neurons (called FN-SOM). The behavior of FN-SOM is investigated with learning for various input data. We confirm that FN-SOM can obtain the m...

In this paper, the idea of creating a system to analyze and improve quality of 2D images is presented. Proposed model operates on self-organizing Kohonen network. For this purpose, the method of image processing and preparation of vectors representing the components of the image are described. Tests on various images were made and presented.