Strongly optimal algorithms and optimal information in estimation problems
Journal of Complexity
Optimality of central and projection algorithms for bounded uncertainty
Systems & Control Letters
Identification and application of bounded-parameter models
Automatica (Journal of IFAC)
Maximum likelihood estimators and worst case optimal algorithms for system identification
Systems & Control Letters
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Orthonormal basis functions for modelling continuous-time systems
Signal Processing
Set-membership binormalized data-reusing LMS algorithms
IEEE Transactions on Signal Processing
On the uniform approximation of discrete-time systems bygeneralized Fourier series
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Rational Basis Functions for Robust Identification from Frequency and Time-Domain Measurements
Automatica (Journal of IFAC)
The size of the membership-set in a probabilistic framework
Automatica (Journal of IFAC)
IEEE Transactions on Information Theory
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In this paper, we study the central and the projection algorithms in membership-set estimation with periodic input signals and orthonormal basis functions for the special case that the number of the estimated parameters equals the input period (or overparameterized model structures). First, we derive explicit formulae for a central algorithm and the diameter of the membership set. Then, we characterize the set of all projection algorithms.