Hierarchical self-programming in recurrent neural networks
نویسندگان
چکیده
منابع مشابه
Hierarchical self-programming in recurrent neural networks
We study self-programming in recurrent neural networks where both neurons (the ‘processors’) and synaptic interactions (‘the programme’) evolve in time simultaneously, according to specific coupled stochastic equations. The interactions are divided into a hierarchy of L groups with adiabatically separated and monotonically increasing time-scales, representing sub-routines of the system programm...
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We study self-programming in recurrent neural networks where both neurons (the 'processors') and synaptic interactions ('the programme') evolve in time simultaneously, according to specific coupled stochastic equations. The interactions are divided into a hierarchy of L groups with adiabatically separated and monotonically increasing timescales , representing sub-routines of the system programm...
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ژورنال
عنوان ژورنال: Journal of Physics A: Mathematical and General
سال: 2002
ISSN: 0305-4470,1361-6447
DOI: 10.1088/0305-4470/35/12/306