Formulation of the MACE filter as a linear associative memory
Shows that the minimum average correlation energy (MACE) filter can be formulated as a linear associative memory (LAM) trained with pre-whitened exemplars. Using this formulation, iterative methods which are numerically stable can be used to obtain the equivalent MACE filter coefficients in the space domain.<<ETX>>