7: Competition and Self-organisation: Kohonen Nets

Understanding Kohonen Networks

Kohonen neural nets are some kind of competitive nets. The most commonly known variants are the Self-Organizing Maps (SOMs) and the Learning Vector Quantization (LVQ). The former model uses an unsupervized learning, the latter is an e cient classi er. This paper tries to give, in simple words, a clear idea about the basis of competitive neural nets and competitive learning emphasizing on the SO...

Self-organisation, metastable states and the ODE method in the Kohonen neural network

Long-Term Time Series Forecasting Using Self-Organizing Maps: the Double Vector Quantization Method

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 long-term trends prediction, with a double application of the Kohonen algorithm. We also consider practical issues for the use of the method.

Time series forecasting: Obtaining long term trends with self-organizing maps

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 ...

Self-organisation can generate the discontinuities in the somatosensory map

The primary somatosensory cortex contains a topographic map of the body surface, with two notable discontinuities—the representation of the face is next to that of the hands, and that of the feet is next to the genitals. Farah [Why does the somatosensory homunculus have hands next to face and feet next to genitals? a hypothesis. Neural Computation 10(8) (1998) 1983–1985] has suggested that thes...