Engineering applications of the self-organizing map

The self-organizing map (SOM) method is a new, powerful software teal for the visualization of high-dimensional data. It concerts complex, nonlinear statistical relationships between high-dimensional data into simple geometric relationships on a low-dimensional display. As if thereby compresses information while preserving the most important topological and metric relationships of the primary data elements on the display, it may also be thought ro produce some kind of abstractions. These two aspects, visualization and abstraction, occur in a number of complex engineering tasks such as process analysis, machine perception, control, and communication. The term self-organizing map signifies a class of mappings defined by error-theoretic consideration. In practice they result in certain unsupervised, competitive learning processes, computed by simple-looking SOM algorithms, The first SOM algorithms were conceived around 1981-1982, and the popularity of the more advanced SOM methods is growing at a steady pace. Many industries have found the SOM-based software tools useful. The most important property of the SOM, orderliness of the input-output mapping, can be utilized for many tasks: reduction of the amount of training data, speeding up learning, nonlinear interpolation and extrapolation, generalization, and effective compression of information for its transmission.