Identification of neurofuzzy models using GTLS parameter estimation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A cumulant based algorithm for the identification of input-output quadratic systems
Automatica (Journal of IFAC)
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The extended generalized total least squares (e-GTLS) method (that consider the special structure of the data matrix) is proposed as one of the bilinear system parameters. Considering that the input is noise free and that bilinear system equation is linear with respect to the output, we extend the GTLS problem. The extended GTLS problem is reduced to an unconstrained minimization problem and is then solved by the Newton-Raphson method. We compare the GTLS method and the extended GTLS method as far as the accuracy of the estimated system parameters is concerned