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Chaotic itinerancy in the oscillator neural network without Lyapunov functions

机译:没有Lyapunov函数的振荡器神经网络中的混沌迭代

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Chaotic itinerancy (CI), which is defined as an incessant spontaneous switching phenomenon among attractor ruins in deterministic dynamical systems without Lyapunov functions, is numerically studied in the case of an oscillator neural network model. The model is the pseudoinverse-matrix version of the previous model [S. Uchiyama and H. Fujisaka, Phys. Rev. E 65, 061912 (2002)] that was studied theoretically with the aid of statistical neurodynamics. It is found that CI in neural nets can be understood as the intermittent dynamics of weakly destabilized chaotic retrieval solutions. (C) 2004 American Institute of Physics.
机译:在振荡器神经网络模型的情况下,对混沌迭代(CI)进行了数值研究,它被定义为在没有Lyapunov函数的确定性动力系统中,吸引子之间不断发生的自发切换现象。该模型是先前模型的伪逆矩阵版本。内山和藤阪H. Rev. E 65,061912(2002)]在理论上借助统计神经动力学进行了研究。发现神经网络中的CI可以理解为弱不稳定混沌检索解的间歇动力学。 (C)2004美国物理研究所。

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