On the Variants of the Self-Organizing Map That Are Based on Order Statistics
Two well-known variants of the self-organizing map (SOM) that are based on order statistics are the marginal median SOM and the vector median SOM. In the past, their efficiency was demonstrated for color image quantization. In this paper, we employ the well-known IRIS data set and we assess their performance with respect to the accuracy, the average over all neurons mean squared error between the patterns that were assigned to a neuron and the neuron’s weight vector, and the Rand index. All figures of merit favor the marginal median SOM and the vector median SOM against the standard SOM. Based on the aforementioned findings, the marginal median SOM and the vector median SOM are used to re-distribute emotional speech patterns from the Danish Emotional Speech database that were originally classified as being neutral to four emotional states such as hot anger, happiness, sadness, and surprise.
KeywordsMean Square Error Weight Vector Input Pattern Rand Index Emotional Speech
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