Efficient Decomposition of Comparison and Its Applications
Valeriu C. Beiu, Jan A. Peperstraete, Joos P. L. Vandewalle, Rudy Lauwereins · The European Symposium on Artificial Neural Networks · 1993
The paper deals with transformation algorithms for decomposing Boolean neural networks (NNs); this being done with a view to possible VLSI implementation of NNs using threshold gates (TGs). We detail a possible tree decomposition for COMPARISON, and show how this can be used for the decomposition of Boolean functions (BFs) belonging to FN,m – the class of BFs of N variables that have exactly m groups of ones. Complexity estimates are given, the results being: (i) linear size; (ii) logarithmic depth; (iii) constant weights; and (iv) constant threshold.