TY - JOUR
T1 - Implementation of a New Neurochip Using Stochastic Logic
AU - Sato, Shigeo
AU - Nemoto, Ken
AU - Akimoto, Shunsuke
AU - Kinjo, Mitsunaga
AU - Nakajima, Koji
PY - 2003/9
Y1 - 2003/9
N2 - Even though many neurochips have been developed and investigated, the best suitable way for implementation has not been known clearly. Our approach is to exploit stochastic logic for various operations required for neural functions. The advantage of stochastic logic is that complex operations can be implemented with a few ordinary logic gates. On the other hand, the operation speed is not so fast since stochastic logic requires certain accumulation time for averaging. But huge integration can be achieved and its reliability is high because all of operations are done on digital circuits. Furthermore, we propose a nonmonotonic neuron realized by stochastic logic, since the nonmonotonic property is efficient for the performance enhancement in association and learning. In this paper, we show the circuit design and measurement results of a neurochip comprising 50 neurons are shown. The advantages of nonmonotonic property and stochasticism are shown clearly.
AB - Even though many neurochips have been developed and investigated, the best suitable way for implementation has not been known clearly. Our approach is to exploit stochastic logic for various operations required for neural functions. The advantage of stochastic logic is that complex operations can be implemented with a few ordinary logic gates. On the other hand, the operation speed is not so fast since stochastic logic requires certain accumulation time for averaging. But huge integration can be achieved and its reliability is high because all of operations are done on digital circuits. Furthermore, we propose a nonmonotonic neuron realized by stochastic logic, since the nonmonotonic property is efficient for the performance enhancement in association and learning. In this paper, we show the circuit design and measurement results of a neurochip comprising 50 neurons are shown. The advantages of nonmonotonic property and stochasticism are shown clearly.
KW - Boltzmann machine (BM)
KW - Large-scale integration (LSI) implementation
KW - Nonmonotonic neuron
KW - Simulated annealing
KW - Stochastic logic
KW - Traveling salesman problem
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U2 - 10.1109/TNN.2003.816341
DO - 10.1109/TNN.2003.816341
M3 - Article
AN - SCOPUS:0242695738
SN - 1045-9227
VL - 14
SP - 1122
EP - 1127
JO - IEEE Transactions on Neural Networks
JF - IEEE Transactions on Neural Networks
IS - 5
ER -