A generalized unstructured artificial neural network architecture: a first study

We present an unstructured neural network based on the mathematics of holographic storage. This work was inspired when we discovered there are similarities between brain waves and the wave propagation and subsequent interference patterns seen in holograms. We then analyzed the mathematics to produce a general mathematical description of the holographic process. From this analysis we are able to show how the holographic process can be used as an associative memory network. Additionally, the process may also be used as a regular feedforward network. The most striking aspect of these networks is that, using the holographic process, the a priori knowledge of the system may be better utilized to tailor the neural network for a particular problem. This aspect, makes this neural network formation process particularly useful for control.