Learning in the context of nonlinear psychophysics: The Gamma Zak Embedding
Robert A. M. Gregson · British Journal of Mathematical and Statistical Psychology · 1993
The problem of how a consistent sensory input can be given an invariant name is addressed within the framework of nonlinear psychophysical theory. In order to link sensory transduction processes to cognitive operations an extension of purely psychophysical modelling is used. A hybrid model of sensory switching, produced by injecting a Λ recursion into a non‐Lipschitzian dynamics evolved by Zak, has the capacity to differentiate inputs and encode inputs into classes, in a form that makes vector inputs to neural networks possible. This is a necessary precursor to learning new sensory‐verbal mappings. The distinction between using piecewise linear models and using continuous nonlinear dynamics in theory construction is emphasized.