TY - GEN
T1 - Robustness of attractor networks and an improved convex corner detector
AU - Nachbar, P.
AU - Schuler, A. J.
AU - Füssl, T.
AU - Nossek, J. A.
AU - Chua, L. O.
N1 - Publisher Copyright:
© 1992 IEEE.
PY - 1992
Y1 - 1992
N2 - By defining several notions of robustness for an attractor network, we aie able to augment previous results about the AdaTron algorithm by explicit values for the robustness of the optimal weights. We show, that the symmetry of a problem is reflected by the invariance of the optimal weights. This enables us to deduce that a convex coiner detection, using a discrete-time Cellular Neural Network (DTCNN), can not be accomplished with just one clock cycle, and we propose an improved convex corner detector.
AB - By defining several notions of robustness for an attractor network, we aie able to augment previous results about the AdaTron algorithm by explicit values for the robustness of the optimal weights. We show, that the symmetry of a problem is reflected by the invariance of the optimal weights. This enables us to deduce that a convex coiner detection, using a discrete-time Cellular Neural Network (DTCNN), can not be accomplished with just one clock cycle, and we propose an improved convex corner detector.
UR - http://www.scopus.com/inward/record.url?scp=85033835080&partnerID=8YFLogxK
U2 - 10.1109/CNNA.1992.274355
DO - 10.1109/CNNA.1992.274355
M3 - Conference contribution
AN - SCOPUS:85033835080
T3 - Proceedings - 2nd International Workshop on Cellular Neural Networks and their Applications, CNNA 1992
SP - 55
EP - 61
BT - Proceedings - 2nd International Workshop on Cellular Neural Networks and their Applications, CNNA 1992
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Workshop on Cellular Neural Networks and their Applications, CNNA 1992
Y2 - 14 October 1992 through 16 October 1992
ER -