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- W2293161514 abstract "Despite the enormous power of present-day computers, digital systems can not respond to real-world events in real time. Biological systems built with very slow chemical transistors, however, are very fast in such tasks like seeing, recognizing, and taking actions. The paper will discuss what we can learn from biological systems and how we can implement the principle using the state-of-the-art silicon technology. Intelligent LSI systems based on the psychological model of a brain are proposed. The system stores the past experience in non-volatile vast analog memories and recall the-most-similar event to a current input using the association device working in the analog/digital-merged decision making principle." @default.
- W2293161514 created "2016-06-24" @default.
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- W2293161514 date "2002-11-23" @default.
- W2293161514 modified "2023-09-25" @default.
- W2293161514 title "Neural microelectronics" @default.
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- W2293161514 doi "https://doi.org/10.1109/iedm.1997.650395" @default.
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