Real-time analog global optimization with constraints: application to the direction of arrival estimation problem

An analog technique for real-time, multivariate, global optimization with constraints is presented. The basic structure is a simple gradient descent loop, where the gradients are computed using an analog neural network. Constraints are implemented using a variation of an idea, where neural networks are also used to implement the required constraint functions. It is shown that the system converges to a stable equilibrium point, which satisfies …