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- W3019345947 abstract "Echo state network (ESN) is a class of recurrent neural network, and is known for drastically reducing the training time by the use of reservoir, a random and fixed network as the input and middle layers. In this paper, we propose a hardware implementation of ESN that uses practical MOSFET-based reservoir. As opposed to existing reservoirs that require additional tuning of network weights for improved stability, our ESN requires no post-training parameter tuning. To this end, we apply the circular law of random matrix to sparse reservoirs to determine a stable and fixed feedback gain. Through the evaluations using Mackey-Glass time-series dataset, the proposed ESN performs successful inference without post parameter tuning." @default.
- W3019345947 created "2020-05-01" @default.
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- W3019345947 date "2020-02-26" @default.
- W3019345947 modified "2023-09-24" @default.
- W3019345947 title "A Tuning-Free Hardware Reservoir Based on MOSFET Crossbar Array for Practical Echo State Network Implementation" @default.
- W3019345947 hasPublicationYear "2020" @default.
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