APPARATUS FOR CONTROLLING THE LEARNING OF A NEURAL NETWORK BASED ON THE PAST RECORDS OF WEIGHT VALUES OF SYNAPTIC CONNECTIONS

The past record of the synaptic weight values set in the learning of a neural network is stored in a weight record memory. The past stored in the weight record memory is supplied to a control unit. If there exists a synaptic connection representing a record of weight values which have been used in a predetermined number of learning processes just prior to the present learning process and which satisfy a predetermined condition, the synaptic weight value used in the succeeding learning processes for the synaptic connection is re-set to a predetermined value by a weight setting unit. That is, the past record of the synaptic weight values is monitored, and the synaptic weight value which has been set in a learning process can be re-set as required.