On constructing threshold networks for pattern classification
Anthony, M.
(2009).
On constructing threshold networks for pattern classification.
In
Franco, L., Elizondo, D. A. & Jerez, J. M.
(Eds.),
Constructive Neural Networks
(pp. 71-82).
Springer Berlin / Heidelberg.
(2009).
On constructing threshold networks for pattern classification.
In
Franco, L., Elizondo, D. A. & Jerez, J. M.
(Eds.),
Constructive Neural Networks
(pp. 71-82).
Springer Berlin / Heidelberg.
This paper describes a method of constructing one-hidden layer feedforward linear threshold networks to represent Boolean functions (or partially-defined Boolean functions). The first step in the construction is sequential linear separation, a technique that has been used by a number of researchers [7, 11, 2]. Next, from a suitable sequence of linear separations, a threshold network is formed. The method described here results in a threshold network with one hidden layer. We compare this approach to the standard approach based on a Boolean function’s disjunctive normal form and to other approaches based on sequential linear separation [7, 11]