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• W2018511121 abstract "Chaotic attractors of discrete-time neural networks include infinitely many unstable periodic orbits, which can be stabilized by small parameter changes in a feedback control. Here we explore the control of unstable periodic orbits in a chaotic neural network with only two neurons. Analytically, a local control algorithm is derived on the basis of least squares minimization of the future deviations between actual system states and the desired orbit. This delayed control allows a consistent neural implementation, i.e. the same types of neurons are used for chaotic and controlling modules. The control signal is realized with one layer of neurons, allowing selective switching between different stabilized periodic orbits. For chaotic modules with noise, random switching between different periodic orbits is observed." @default.
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• W2018511121 date "1998-01-01" @default.
• W2018511121 modified "2023-10-16" @default.
• W2018511121 title "Attractor switching by neural control of chaotic neurodynamics" @default.
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• W2018511121 doi "https://doi.org/10.1088/0954-898x_9_4_009" @default.
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