Abstract
The capacity of a 1-layer net is limited compared to a multilayer net. However, there is no explicit rule for optimal structuring and training of a multilayer net. Thus iterative methods are usually used. Here we propose a systematic way to build and train a special multilayer network called a recursive branching network. The theory behind this network is presented along with experimental work done on a VOWEL data set. (Author)