Reduced-complexity equaliser for nonlinear channels

Abstract

The generalised cerebellar model arithmetic computer (GCMAC) network is applied to the problem of adaptive equalisation of nonlinear channels. The GCMAC-based equaliser is compared with other well-known structures such as the Volterra filter and the multi-layer perceptron. The results obtained show the effectiveness of the proposed structure for compensating strong nonlinearities.