CNN implemented by nonlinear phase dynamics in nanoscale processes

We discuss CNNs in which the states are defined by the electrical phase of a dynamic physical process, such as electron tunneling in ultra-small junctions or integrate-and-fire processes in nanoscale structures or molecules. Such processes produce impulsive "neuron-like" waveforms which can be coupled to nearest neighbors in a 1D, 2D, or 3D array. Input data can be represented by the distribution of dc bias level, initial charge, or coupling strength within the array. Information processing can be realized through the nonlinear dynamics produced by interactions between elements, which give rise to an evolution of complex patterns in the phase-state. In this paper, we discuss information processing for a model physical system based on Coulomb blockade in a 2D array of ultra-small tunnel junctions.