Amorphous Computational Material (ACM) is a concept of an active material that can sense its environment and, due to its cognitive capabilities, react “intelligently” to those changes. In this paper, We demonstrate the feasibility of utilizing water hammer as a form of directed actuation. We show a novel concept of a Synthetic Neural Network, a type of an organic neuromorphic architecture modeled after Artificial Neural Network, which is used for a distributed cognition purposes for ACM. A simulation of the SNN is shown to accurately predict the directionality of water hammer propulsion.
LEGION-based image segmentation by means of spiking neural networks using normalized synaptic weights implemented on a compact scalable neuromorphic architecture