HARDWARE IMPLEMENTATION OF NEURAL NETWORKS IN JAPAN

In this paper, research activities on hardware implementation of neural networks in Japan are reviewed. In Japan, digital, analog, and optoelectronic technologies have been applied to neural network hardware. Among them, digital approach is the most prevailing. Several types of on-chip BP learning have been implemented in digital hardware, and 2.3 GCUPS (Giga Connection Updates Per Second) learning speed has already been attained. Most of the largest Japanese electronic comPanies have developed this kind of system and have run various neural networks on it. Although the most prevailing approach is digital, intensive researches on analog and optoelectronic approaches are also carried out. For analog approach, 28 GCUPS on-chip learning speed and 1 TCPS (Tera Connections Per Second) processing speed for Boltzmann machine with 1 bit digital output have been obtained. For the optoelectronic approach, although the network size is small, 640 MCUPS BP learning speed has been attained.