Adaptive knot Placement for Nonparametric Regression

We show how an "Elman" network architecture, constructed from recurrently connected oscillatory associative memory network mod(cid:173) ules, can employ selective "attentional" control of synchronization to direct the flow of communication and computation within the architecture to solve a grammatical inference problem. Previously we have shown how the discrete time "Elman" network algorithm can be implemented in a network completely described by continuous ordinary differential equations. The time steps (ma(cid:173) chine cycles) of the system are implemented by rhythmic variation (clocking) of a bifurcation parameter. In this architecture, oscilla(cid:173) tion amplitude codes the information content or activity of a mod(cid:173) ule (unit), whereas phase and frequency are used to "softwire" the network. Only synchronized modules communicate by exchang(cid:173) ing amplitude information; the activity of non-resonating modules contributes incoherent crosstalk noise.