METHOD AND DEVICE FOR SIMULATING NEURAL NETWORK COMPLETELY IN PARALLEL BY USING DIGITAL INTEGRATED CIRCUIT

摘要

PURPOSE: To speed up the learning of a multi-layered neural network by performing calculation for correcting synapsis weight in parallel and also carrying out calculation for correcting a virtual target in parallel. ;CONSTITUTION: A neuron inputs an input pattern O^k from a precedent layer, multiplies a presynapsis virtual target vector T^k by a synapsis weight vector W^k, and performs the sigmoid transformation of their sum to calculate an input O^k+1 to the following layer. Here, (k) is the number of layers. Then the weight W^k is calculated by using an error between the input O^k+1 to the following layer and the virtual target T^k+1 of the following layer and the virtual target T^k to be updated. Then the virtual target T^k is calculated by using presynapsis and postsynapsis virtual targets T^k and T^k+1, presynapsis and postsynapsis input patterns O^k and O^k+1, and the updated weight W^k and updated. The calculating processes in the respective steps are all performed in parallel.;COPYRIGHT: (C)1994,JPO&Japio