| 摘要 |
A data processing system has a memory for realizing large-scale and high-speed parallel distributed processing and, especially, a data processing system for neural network processing. The neural network processing system comprises: a memory circuit for storing neuron output values, connection weights, the desired values of outputs, and data necessary for learning; an input/output circuit for writing or reading data in or out of said memory circuit; a processing circuit for performing a processing for determining the neuron outputs such as the product, sum and nonlinear conversion of the data stored in said memory circuit, a comparison of the output value and its desired value, and a processing necessary for learning; and a control circuit for controlling the operation of the memory circuit, the input/output circuit and the processing circuit. The processing circuit includes at least one of an address, a multiplier, a nonlinear transfer function circuit and a comparator so that at least a portion of the processing necessary for determining the neuron output values such as the product of sum may be accomplished in parallel. Moreover, these circuits are shared among a plurality of neurons and are operated in a time sharing manner to determine the plural neuron output values. Still moreover, the aforementioned comparator compares the neuron output value determined and the desired value of the output in parallel.
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