The architecture is quite compact compared to most models of pattern recognition that require very large computing power. It lacks logical relationships and aggregation of conditions in fuzzy systems.
Its practical value is in its high flexibility, ease of implementation and time efficiency of the method. High learning speed and universal approximating properties of the proposed network will be especially useful when processing multidimensional vector argument functions.
Listed in what follows are the main results obtained in this chapter.
- The classification problem of the multidimensional overlapping of objects reduces to a fuzzy modification of pattern recognition tasks.
- Based on the promising developments in the field of cellular self-organizing ...
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