2013 Special Issue: Hierarchical random cellular neural networks for system-level brain-like signal processing

摘要: Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's state is described by a trajectory evolving high-dimensional space. We introduce hierarchy of random cellular automata as the mathematical tools to describe spatio-temporal dynamics cortex. corresponding brain model called neuropercolation which has distinct advantages compared traditional models differential equations, especially describing discontinuities form phase transitions. Phase transitions demarcate singularities operations at critical conditions, viewed hallmarks higher awareness experience. introduced Monte-Carlo simulations obtained parallel computing point importance computer implementations very large-scale integration (VLSI) analog platforms.