Map estimation and the multilayer perceptron

The utility of linear transformations to compress data efficiently for purposes of estimation via neural net techniques is describing. A method for comparing transforms based upon transform domain error bounds is reviewed, and a method for improving the transform through re-ordering is described. The bounds also give clues as to how many transform coefficients are necessary and when training can be stopped. They also help to understand why it is often productive to have separate multilayer perceptrons (MLPs) for each parameter to be estimated