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Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method.

, , , , and . CDC, page 265-270. IEEE, (2014)

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nonlinear black-box modeling in system identification: a unified overview, , , , , , , and . Automatica, (1995)Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyperparameter Estimator., , , and . IEEE Trans. Autom. Control., 68 (12): 7224-7239 (December 2023)On the choice of norms in system identification., , and . IEEE Trans. Autom. Control., 41 (9): 1367-1372 (1996)Implementation of algorithms for tuning parameters in regularized least squares problems in system identification., and . Autom., 49 (7): 2213-2220 (2013)On global identifiability for arbitrary model parametrizations., and . Autom., 30 (2): 265-276 (1994)Variance properties of a two-step ARX estimation procedure., and . ECC, page 1840-1845. IEEE, (2001)Frequency-domain identification of continuous-time ARMA models from sampled data., and . Autom., 45 (6): 1371-1378 (2009)Decomposition methods for solving least-squares parameter estimation., , and . IEEE Trans. Signal Process., 44 (11): 2847-2852 (1996)Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method., , , , and . CDC, page 265-270. IEEE, (2014)Kernel-based model order selection for identification and prediction of linear dynamic systems., , and . CDC, page 5174-5179. IEEE, (2013)