Spatial-temporal properties of artificial dendritic trees

The author describes the electronic architecture and dynamic signal processing capabilities of artificial dendritic trees which comprise simple microcircuits of artificial synapses closely modeled after their biological namesakes. It is demonstrated that powerful processing of dynamic signals can be accomplished using these structures, which do not use complex computational devices such as multipliers, adders, look-up-tables, or microprocessors. Conventional weights are replaced with connections which, when combined with the nonlinear behavior of nearby synapses and the nearly linear behavior of widely separated synapses, provide an arbitrarily precise signal processing sensitivity. The connection space is extremely large and is a factorial function of the number of synapses and sensory inputs. Because of the electrical properties of the artificial dendritic tree and the very large connection space, the circuits are virtually immune to variations in the fabrication process, which makes them suitable for implementing on a wafer scale