TY - JOUR
T1 - On the separating capability of cellular neural networks
AU - Osuna, J. A.
AU - Moschytz, G. S.
PY - 1996
Y1 - 1996
N2 - The cellular neural network is able to perform different image-processing tasks depending on the template values, i.e. the network parameters, used. In the case of linear templates the parameter space is divided into different regions by hyperplanes. Every region is associated with a task, such that all points within that region let the cellular neural network perform the desired task. In this paper a lower and an upper bound for the number of regions that can be separated with binary-input cellular neural networks are given, thus answering the question of how many different-tasks such a cellular neural network can perform.
AB - The cellular neural network is able to perform different image-processing tasks depending on the template values, i.e. the network parameters, used. In the case of linear templates the parameter space is divided into different regions by hyperplanes. Every region is associated with a task, such that all points within that region let the cellular neural network perform the desired task. In this paper a lower and an upper bound for the number of regions that can be separated with binary-input cellular neural networks are given, thus answering the question of how many different-tasks such a cellular neural network can perform.
UR - http://www.scopus.com/inward/record.url?scp=85087190644&partnerID=8YFLogxK
U2 - 10.1002/(sici)1097-007x(199605/06)24:3<253::aid-cta913>3.3.co;2-0
DO - 10.1002/(sici)1097-007x(199605/06)24:3<253::aid-cta913>3.3.co;2-0
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AN - SCOPUS:85087190644
SN - 0098-9886
VL - 24
SP - 253
EP - 259
JO - International Journal of Circuit Theory and Applications
JF - International Journal of Circuit Theory and Applications
IS - 3
ER -