scholarly journals Learning state space trajectories in recurrent neural networks

1989 ◽  
Author(s):  
Pearlmutter
Keyword(s):  
Neural Networks ◽  
State Space ◽  
Recurrent Neural Networks ◽  
Space Trajectories

scholarly journals Reservoir computing and the Sooner-is-Better bottleneck

2016 ◽  
Vol 39 ◽  
Author(s):  
Stefan L. Frank ◽  
Hartmut Fitz
Keyword(s):  
Neural Networks ◽  
State Space ◽  
Recurrent Neural Networks ◽  
Random Point ◽  
High Dimensional ◽  
Reservoir Computing ◽  
Current Input ◽  
Dimensional State Space ◽  
Language Input

AbstractPrior language input is not lost but integrated with the current input. This principle is demonstrated by “reservoir computing”: Untrained recurrent neural networks project input sequences onto a random point in high-dimensional state space. Earlier inputs can be retrieved from this projection, albeit less reliably so as more input is received. The bottleneck is therefore not “Now-or-Never” but “Sooner-is-Better.”

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