Here we propose a novel fractal-graph approach to complement the usual graph-theoretic methods which are critically limited when applied to large networks with their continued growth and dynamic characteristics. This fractal-graph approach uses the sometimes hidden underlying order inherent in typical networks and focusses on their global properties. This allows a prescription both for the growth of these complex networks and a framework for characterizing them in new ways.

A novel method of random array synthesis is presented. This new method relies on the application of the underlying self-similarity inherent in random fractals to the problem of antenna array theory. Several examples demonstrate the synthesis procedure and its usefulness in producing robust, low sidelobe arrays.