Equalisation using neural networks

Neural networks offer a number of advantages over other architectures: they are capable of generalisation, and because of their strong-interconnectivity, they are capable of offering real-time solutions to complex optimisation problems. The authors have applied a multilayer feed-forward network of perceptrons to the problem of equalisation in digital communication systems. In the absence of rigorous analytical bounds, they have simulated the neural equaliser and present results of its performance in comparison to the linear transversal equaliser implemented on the A100 DSP device