R. Helminen

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The Self-Organizing Map (SOM) is a powerful neural network method for the analysis and visualization of high-dimensional data. It maps nonlinear statistical relationships between high-dimensional measurement data into simple geometric relationships, usually on a two-dimensional grid. The mapping roughly preserves the most important topological and metric(More)
The effect of active and passive finger movement on cutaneous sensitivity to nonpainful electric stimulation was studied in 7 healthy human subjects. Active and passive finger movement produced a suppression of threshold stimuli, whereas the amplitude discrimination of suprathreshold stimuli was enhanced during passive but not active movement.
The Self-Organizing Map (SOM) is a powerful neural network method for the analysis and visualisation of high-dimensional data. In this paper, the SOM algorithm is applied to the analysis of the technology of world paper and pulp industry. It is seen that the method can be used on environmental, technological and nancial data to produce a comprehensive view(More)
The purpose of this study was to find out whether the finger movement-induced modulation of cutaneous discrimination thresholds varies with the intensity level of the test stimulation in various movement conditions. The effect of active and passive finger movement on cutaneous sensitivity to nonpainful electrical stimulation of threshold and suprathreshold(More)
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