Improved neural networks for analog to digital conversion

The problem of designing a neural network which will give the correct binary representation of any given real number is studied. The proposed neural network almost always has a single, globally attractive, asymptotically stable equilibrium, regardless of the input current. Hence, irrespective of the initial conditions of the network, it will always yield a correct binary representation of the given input