Title :
The K1-map reduction for pattern classifications
Author :
Hsu, Tsong-Chih ; Wang, Sheng-De
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fDate :
6/1/1997 12:00:00 AM
Abstract :
A shortcut hand-reduction method known as the Karnaugh map (K map) is an efficient way of reducing Boolean functions to a minimum form for the purpose of minimizing hardware requirements. In this paper, by applying the prime group and the essential prime group concepts of the K maps to pattern classification problems, the K1-map reduction method is proposed. The K1-map reduction method can be used to design restricted Coulomb energy networks and to determine the number of hidden units problems in a systematic manner
Keywords :
Boolean functions; feedforward neural nets; group theory; learning (artificial intelligence); pattern classification; Boolean functions; K1-map reduction; Karnaugh map; RBF neural network; one class one network; pattern classifications; prime group; restricted Coulomb energy networks; Boolean functions; Clustering algorithms; Computer architecture; Convergence; Electrostatics; Hardware; Pattern classification; Psychology; Radial basis function networks; Space charge;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
