Gro¨bner bases: a computational approach to commutative algebra
Gro¨bner bases: a computational approach to commutative algebra
On global identifiability for arbitrary model parametrizations
Automatica (Journal of IFAC)
Neural network-based analog fault diagnosis using testability analysis
Neural Computing and Applications
Protocol and fault detection design for nonlinear networked control systems
IEEE Transactions on Circuits and Systems II: Express Briefs
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In this paper, a symbolic procedure for ambiguity-group determination, based on the a priori identifiability concept, is proposed. The method starts from the analysis of the occurrence of circuit parameters in the coefficients of the input/output relationship in order to select the potential canonical ambiguity groups. This first step allows one to strongly reduce the problem complexity. In a second step, the obtained nonlinear system that imposes the ambiguity conditions is solved, resorting to Gröbner bases theory. Both of these steps are completely symbolic, thus avoiding round-off errors. Furthermore, the method can be applied to both linear and nonlinear circuits. An alternative approach is also proposed, which extends to nonlinear circuits a method presented in the literature, which can be directly applied only to linear circuits. The methods are illustrated by means of benchmarks regarding well-known linear and nonlinear circuits.