Stability criteria for the contextual emergence of macrostates in neural networks
| Abstract | More than thirty years ago, Amari and colleagues proposed a statistical framework for identifying structurally stable macrostates of neural networks from observations of their microstates. We compare their stochastic stability criterion with a deterministic stability criterion based on the ergodic theory of dynamical systems, recently proposed for the scheme of contextual emergence and applied to particular inter-level relations in neuroscience. Stochastic and deterministic.. | |||||||||
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Michael Lamport Commons (2008). Stacked Neural Networks Must Emulate Evolution's Hierarchical Complexity. World Futures 64 (5 - 7):444 – 451.
Enrico Blanzieri (1997). Dynamical Learning Algorithms for Neural Networks and Neural Constructivism. Behavioral and Brain Sciences 20 (4):559-559.
Gualtiero Piccinini (2008). Some Neural Networks Compute, Others Don't. Neural Networks 21 (2-3):311-321.
Harald Atmanspacher (2007). Contextual Emergence From Physics to Cognitive Neuroscience. Journal of Consciousness Studies 14 (1-2):18-36.
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