Title :
On the number of multilinear partitions and the computing capacity of multiple-valued multiple-threshold perceptrons
Author :
Ngom, Alioune ; Stojmenovic, Ivan ; Zunic, Jovisa
Author_Institution :
Comput. Sci. Dept., Univ. of Windsor, Ont., Canada
fDate :
5/1/2003 12:00:00 AM
Abstract :
We introduce the concept of multilinear partition of a point set V⊂Rn and the concept of multilinear separability of a function f:V→K={0,...,k-1}. Based on well-known relationships between linear partitions and minimal pairs, we derive formulae for the number of multilinear partitions of a point set in general position and of the set K2. The (n,k,s)-perceptrons partition the input space V into s+1 regions with s parallel hyperplanes. We obtain results on the capacity of a single (n,k,s)-perceptron, respectively, for V⊂Rn in general position and for V=K2. Finally, we describe a fast polynomial-time algorithm for counting the multilinear partitions of K2.
Keywords :
computational complexity; pattern recognition; perceptrons; computing capacity; fast polynomial-time algorithm; linear partitions; minimal pairs; multilinear partitions; multilinear separability; multiple-valued multiple-threshold perceptrons; Computational modeling; Computer science; Computer simulation; Information technology; Logic devices; Logic functions; Partitioning algorithms; Polynomials; Power system modeling; Transfer functions;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2003.810598