Model of the neuronal net for detection of single bars and cross-like figures
The model of the discrete net for detection of cross-like figures is offered. The properties of the simulated detector of cross are investigated and compared with real cross-detectors found in the cat primary visual cortex. It is shown that an excitatory convergence from some neurons with different preferred orientations and an amplifying mechanism is necessary for effective detection of a cross-like figure.
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