Title :
Neural network construction via a linear program
Author :
Pollatschek, M.A.
Author_Institution :
Fac. of Ind. Eng. & Manage., Technion-Israel Inst. of Technol., Haifa, Israel
Abstract :
A procedure with polynomial complexity is proposed to construct a feed-forward neural network with binary inputs and a single binary output. The problem is formulated as one in linear inequalities and is solved by a modification of the primal simplex algorithm. We claim that it finds an acceptably low number of artificial neurons in the hidden layer or, equivalently, the number of separating hyperplanes.
Keywords :
backpropagation; feedforward neural nets; linear programming; multilayer perceptrons; artificial neurons; binary inputs; feedforward neural network; hidden layer; linear inequalities; linear program; neural network construction; polynomial complexity; primal simplex algorithm; separating hyperplanes; single binary output; Artificial neural networks; Biological neural networks; Engineering management; Feedforward neural networks; Feedforward systems; Industrial engineering; Neural networks; Neurons; Polynomials; Technology management;
Conference_Titel :
Electrical and Electronics Engineers in Israel, 1995., Eighteenth Convention of
Conference_Location :
Tel Aviv, Israel
Print_ISBN :
0-7803-2498-6
DOI :
10.1109/EEIS.1995.514163
