  Artificial Neural Networks(ANN) has been phenomenally successful on various
pattern recognition tasks. However, the design of neural networks rely heavily
on the experience and intuitions of individual developers. In this article, the
author introduces a mathematical structure called MLP algebra on the set of all
Multilayer Perceptron Neural Networks(MLP), which can serve as a guiding
principle to build MLPs accommodating to the particular data sets, and to build
complex MLPs from simpler ones.
