TY - JOUR
T1 - Complexity of perceptron recognition for a class of geometric patterns
AU - Aracena, Julio
AU - Goles, Eric
N1 - Funding Information:
We thank AndreCs Moreira for carefully reading the manuscript and suggesting helpful improvements. This work was partially supported by French Cooperation (J.A., E.G.), ECOS, FONDAP program on Discrete Mathematics (E.G.) Conicyt by doctoral scholarship (J.A.), Fondecyt Project 1970398 (E.G.) and Centro de Modelamiento MatemC atico, UMR 2071 CNRS-UChile.
PY - 2003/4/18
Y1 - 2003/4/18
N2 - In this paper, we study the recognition complexity of discrete geometric figures (rectangles, squares, circles, ellipses) on a retina by diameter-limited and order-restricted perceptrons. We construct a diameter-limited recognition perceptron for the family of rectangles, beginning with local configurations, which is different from the one shown by Minsky et al. (Perceptrons: An Introduction to Computational Geometry, extended edition, MIT Press, Cambridge, MA, 1988). In addition, we demonstrate the nonexistence of diameter-limited recognition perceptrons for squares, circles and ellipses. Finally, for squares and ellipses we construct an order-restricted perceptron with constant coefficients, using an original technique which decomposes the characterization of the figures into local and global features.
AB - In this paper, we study the recognition complexity of discrete geometric figures (rectangles, squares, circles, ellipses) on a retina by diameter-limited and order-restricted perceptrons. We construct a diameter-limited recognition perceptron for the family of rectangles, beginning with local configurations, which is different from the one shown by Minsky et al. (Perceptrons: An Introduction to Computational Geometry, extended edition, MIT Press, Cambridge, MA, 1988). In addition, we demonstrate the nonexistence of diameter-limited recognition perceptrons for squares, circles and ellipses. Finally, for squares and ellipses we construct an order-restricted perceptron with constant coefficients, using an original technique which decomposes the characterization of the figures into local and global features.
KW - Discrete figures
KW - Perceptron
KW - Recognition
UR - http://www.scopus.com/inward/record.url?scp=0037453350&partnerID=8YFLogxK
U2 - 10.1016/S0304-3975(01)00266-3
DO - 10.1016/S0304-3975(01)00266-3
M3 - Article
AN - SCOPUS:0037453350
SN - 0304-3975
VL - 299
SP - 65
EP - 79
JO - Theoretical Computer Science
JF - Theoretical Computer Science
IS - 1-3
ER -