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Table 1 Comparative characteristics of means of the parallel hierarchical transformation

From: Modeling of a method of parallel hierarchical transformation for fast recognition of dynamic images

Number Parameter Indices
Known soft hardware (imitational modeling based on MLP and RBF networks[23]) Known soft hardware (imitational modeling based on neural-like network technology[22]) Known soft hardware (central processor, PH transformation method based on the Q-decomposition[19]) Suggested soft hardware (graphical processor, method of the PH network training based on the normalizing equation)
1 Average size of good route fragments (%) 70 74 50 18
2 Average value of correct recognition (%) 92 92,5 84,8 94
3 Accuracy of the energy center determination, decomposition elements 1.5 1.5 1.2 0.01
4 Average recognition time of network processing(s) - - 8.4 1.52
5 Average time of preliminary processing of route fragments(s) - - 3.32 0.6