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• W2050076818 abstract "It has been known for a short time that a class of recurrent neural networks has universal computational abilities. These networks can be viewed as iterated piecewise-linear maps in a high-dimensional space. In this paper, we show that similar systems in dimension two are also capable of universal computations. On the contrary, it is necessary to resort to more complex systems (e.g., iterated piecewise-monotone maps) in order to retain this capability in dimension one." @default.
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• W2050076818 date "1994-09-01" @default.
• W2050076818 modified "2023-10-11" @default.
• W2050076818 title "Computability with low-dimensional dynamical systems" @default.
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• W2050076818 doi "https://doi.org/10.1016/0304-3975(94)90229-1" @default.
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