An Exact and Direct Analytical Method for the Design of Optimally Robust CNN Templates

An Exact and Direct Analytical Method for the Design of Optimally Robust CNN Templates (1999)

by Martin Hänggi , George S. Moschytz

Venue:	IEEE TRANS. CIRCUITS & SYST.--I
Citations:	4 - 2 self

User correction supplied by mph

Datum	Value	Source
TITLE	An Exact and Direct Analytical Method for the Design of Optimally Robust CNN Templates	user correction - Legacy Corrections
AUTHOR NAME	Martin Hänggi	user correction
AUTHOR NAME	George S. Moschytz	user correction
ABSTRACT	In this paper, we present an analytical design approach for the class of bipolar cellular neural networks (CNN's) which yields optimally robust template parameters. We give a rigorous definition of absolute and relative robustness and show that all well-defined CNN tasks are characterized by a finite set of linear and homogeneous inequalities. This system of inequalities can be analytically solved for the most robust template by simple matrix algebra. For the relative robustness of a task, a theoretical upper bound exists and is easily derived, whereas the absolute robustness can be arbitrarily increased by template scaling. A series of examples demonstrates the simplicity and broad applicability of the proposed method.	user correction
YEAR	1999	INFERENCE
VENUE	IEEE TRANS. CIRCUITS & SYST.--I	user correction
VENUE TYPE	JOURNAL	INFERENCE
PAGES	304--311	INFERENCE
VOLUME	46	INFERENCE
NUMBER	2	user correction
CITATIONS	28 found	ParsCit 1.0