Least-mean-log-likelihood adaptive algorithm in single-layer perceptron based communication channel equalisation

This paper presents a novel approach to adapting the weights of single-layer perceptron based communication channel equalisers, using the log-likelihood cost function and the resulting least-mean-log-likelihood adaptive algorithm. It provides promising theoretical and experimental results, illustrating that developing equalisers following this approach allows faster convergence, lower estimation error and better bit error rate performance in comparison with the traditional Rosenblatt (1962) and back-propagation algorithms.