Abstract
Neural networks built of Hodgkin–Huxley neurons were examined. The structure and behavior of these nets was intended to be similar to liquid state machines. They could effectively process different input signals (i.e. geometrical patterns shown to artificial eye). The analysis of output responses was performed in two ways: by means of artificial neural network and by calculating informational entropy.
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