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A neural network model for the developmental process of hypercomplex cells
By: Nagano, T.; Miyajima, S.;
1983 / IEEE
This item was taken from the IEEE Periodical ' A neural network model for the developmental process of hypercomplex cells ' A self-organizing neural network model is proposed which gives a possible implementation of the developmental process of hypercomplex cells in the mammalian visual cortex. It is composed of connections from complex cells to hypercomplex cells via an excitatory fixed synapse or an inhibitory modifiable synapse. Two types of receptive fields termed `single-stopped' and `double-stopped' are formed from the same network. The relation between values of parameters in the model and the type of receptive fields is made clear.
Single Stopped Fields
Double Stopped Fields
Self-organizing Neural Network Model
Mammalian Visual Cortex
Excitatory Fixed Synapse
Inhibitory Modifiable Synapse
Biological System Modeling
Signal Processing And Analysis