Matrix inversion can be considered as an optimization. We have demonstrated that this problem can be rapidly solved by highly interconnected simple neuron-like processors. A network for matrix inversion based on the concept of Hopfield's neural network is designed, and implemented with electro-optic hardware. Binary coded optical vector-matrix multiplier is used. Notable features of this network are potential speed due to parallel processing, and robustness against variations of device parameters.
