Magnetic cellular nonlinear network with spin wave bus for image processing

We describe and analyze a cellular nonlinear network based on magnetic nanostructures for image processing. The network consists of magneto-electric cells integrated onto a common ferromagnetic film–spin wave bus. The magneto-electric cell is an artificial two-phase multiferroic structure comprising piezoelectric and ferromagnetic materials. A bit of information is assigned to the cell’s magnetic polarization, which can be controlled by the applied voltage. The information exchange among the cells is via the spin waves propagating in the spin wave bus. Each cell changes its state as a combined effect: magneto-electric coupling and the interaction with the spin waves. The distinct feature of a network with a spin wave bus is the ability to control the inter-cell communication by an external global parameter — magnetic field. The latter makes it possible to realize different image processing functions on the same template without rewiring or reconfiguration. We present the results of numerical simulations illustrating image filtering, erosion, dilation, horizontal and vertical line detection, inversion and edge detection accomplished on one template by the proper choice of the strength and direction of the external magnetic field. We also present numerical assets on the major network parameters such as cell density, power dissipation and functional throughput, and compare them with the parameters projected for other nano-architectures such as CMOL-CrossNet, Quantum-Dot Cellular Automata, and Quantum Dot-Image Processor. Potentially, the utilization of spin wave phenomena at the nanometer scale may provide a route to low-power consumption and functional logic circuits for special task data processing.