Title :
A convex hull algorithm for neural networks
Author_Institution :
Univ. of Southern California, Los Angeles, CA, USA
fDate :
11/1/1989 12:00:00 AM
Abstract :
A convex hull algorithm for neural networks is presented. It is applicable in both two and three dimensions and has a time complexity of O(N) for the offline case, O(log N) for the online case in two dimensions, and O(hN), O(N), respectively, for three dimensions (h is the number of faces in the convex hull). The constant bounding the complexity is expected to be very small
Keywords :
computational complexity; neural nets; constant; convex hull algorithm; neural networks; offline case; online case; time complexity; Circuits and systems; Computational geometry; Image processing; Motion planning; Multi-layer neural network; Neural networks; Pattern recognition; Process planning; Robots; Rubber;
Journal_Title :
Circuits and Systems, IEEE Transactions on
