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- W3100504110 endingPage "1690" @default.
- W3100504110 startingPage "1669" @default.
- W3100504110 abstract "Artificial intelligence memory is expected to acquire, calculate, and analyze a large amount of logical information and data in time to dynamically respond to artificial neural networks. It is the most promising candidate for realizing a new hardware artificial intelligence architecture that mimics biological neural networks. However, the research on artificial intelligence memory is still in the initial stage, and there are some unresolved bottlenecks for the preparation of artificial intelligence memory devices. Such as it require external power supplements for the operating of memory devices, resulting in high power consumption and difficulty in real-time neuromorphic computing. Fortunately, self-powered memory devices can perfectly solve the above problems. In this Review, we have systemically summarized the current development on material, integration, and technology for the self-powered memory application, as well as provide the prospect, suggestion, and optimization method for neuromorphic computing and artificial intelligence with self-powered memory." @default.
- W3100504110 created "2020-11-23" @default.
- W3100504110 creator A5007299136 @default.
- W3100504110 creator A5024894468 @default.
- W3100504110 creator A5035048973 @default.
- W3100504110 creator A5046947749 @default.
- W3100504110 creator A5070444228 @default.
- W3100504110 date "2020-11-17" @default.
- W3100504110 modified "2023-10-12" @default.
- W3100504110 title "Self-Powered Memory Systems" @default.
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