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cobICA: A concentration-based, immune-inspired algorithm for ICA over Galois fields

An interesting and recent application of population-based metaheuristics resides in an unsupervised signal processing task: independent component analysis (ICA) over finite fields. Based on a state-of-the-art immune-inspired method, this work proposes a new ICA algorithm for finite fields of arbitrary order that employs mutation and local search operators specifically customized to the problem domain. The results obtained with the new technique indicate that the proposal is effective in performing component separation, and the analysis includes a preliminary study on image separation.