Generalized minimum probability of symbol error adaptive equalization

Expected loss or Bayes risk is taken as a criterion for adaptive linear equalization. In this paper loss functions are chosen to weight more serious error events more heavily than less serious events and correct decision. New adaptive algorithms are derived leading to faster convergence and lower steady state error rates than previously proposed error rate minimizing algorithms.