| 1473 - 1473 |
Guest editorial; Special issue on system identification
Ljung L, Vicino A |
| 1477 - 1489 |
On sampled-data models for nonlinear systems
Yuz JI, Goodwin GC |
| 1490 - 1500 |
Application of structured total least squares for system identification and model reduction
Markovsky I, Willems JC, Van Huffel S, De Moor B, Pintelon R |
| 1501 - 1508 |
Control-oriented model validation and errors quantification in the l(1) setup
Sokolov VF |
| 1509 - 1519 |
Subspace identification of Hammerstein systems using least squares support vector machines
Goethals I, Pelckmans K, Suykens JAK, De Moor B |
| 1520 - 1533 |
A Bayesian approach to identification of hybrid systems
Juloski AL, Weiland S, Heemels WPMH |
| 1534 - 1549 |
Input design via LMIs admitting frequency-wise model specifications in confidence regions
Jansson H, Hjalmarsson H |
| 1550 - 1566 |
A convex analytic approach to system identification
Saligrama V |
| 1567 - 1580 |
A bounded-error approach to piecewise affine system identification
Bemporad A, Garulli A, Paoletti S, Vicino A |
| 1581 - 1596 |
Maximum-likelihood parameter estimation of bilinear systems
Gibson S, Wills A, Ninness B |
| 1597 - 1602 |
On the role of prefiltering in nonlinear system identification
Spinelli W, Piroddi L, Lovera M |
| 1602 - 1606 |
Kernel based partially linear models and nonlinear identification
Espinoza M, Suykens JAK, De Moor B |
| 1606 - 1611 |
Model quality in identification of nonlinear systems
Milanese M, Novara C |
| 1612 - 1617 |
Strong consistency of recursive identification for Hammerstein systems with discontinuous piecewise-linear memoryless block
Chen HF |
| 1617 - 1622 |
Identification of IIR Wiener systems with spline nonlinearities that have variable knots
Hughes MC, Westwick DT |
| 1622 - 1628 |
A nonlinear least-squares approach for identification of the induction motor parameters
Wang KY, Chiasson J, Bodson M, Tolbert LM |
| 1629 - 1634 |
Subspace based approaches for Wiener system identification
Raich R, Zhou GT, Viberg M |
