Recursive Construction of Periodoc Steady State for Neural Networks

Abstract : We present a strategy in order to build neural networks with long steady state periodic behavior. This strategy allows us to obtain 2^n non equivalent neural networks of size n, when the equivalence relation is the dynamical systems one. As a particular case, we build a neural networks with n neurons admitting a cycle of period 2^n.
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Martin Matamala. Recursive Construction of Periodoc Steady State for Neural Networks. [Research Report] LIP RR-1993-23, Laboratoire de l'informatique du parallélisme. 1993, 2+20p. ⟨hal-02101956⟩

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