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Hardware Implementation of a DBM Network with Non-monotonic Neurons
IEICE TRANSACTIONS on Information and Systems Vol.E85-D No.3 pp.558-567
Publication Date: 2002/03/01
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Biocybernetics, Neurocomputing
Full Text: PDF(2.8MB)
In this paper, we report a study on hardware implementation of a Deterministic Boltzmann Machine (DBM) with non-monotonic neurons (non-monotonic DBM network). The hardware DBM network has fewer components than other neural networks. Results from numerical simulations show that the non-monotonic DBM network has high learning ability as compared to the monotonic DBM network. These results show that the non-monotonic DBM network has large potential for the implementation of a high functional neurochip. Then, we design and fabricate a neurochip of the non-monotonic DBM network of which measurement confirms that the high-functional large-scale neural system can be realized on a compact neurochip by using the non-monotonic neurons.