Publications-TP

103 entries « ‹ 3 of 6 › »
41.

R J C van Esch; S Shi; A Bernas; Zinger Z.; A P Aldenkamp; P M J Van den Hof

A Bayesian method for inference of effective connectivity in brain networks for detecting the Mozart effect Journal Article

In: Computers in Biology and Medicine, 2020.

| Links:

42.

V C Rajagopal

Learning local modules in dynamic networks without prior topology information Masters Thesis

Eindhoven University of Technology, 2020, (MSc Graduation report).

| Links:

43.

H H M Weerts; J Linder; M Enqvist; P M J Van den Hof

Abstractions of linear dynamic networks for input selection in local module identification Journal Article

In: Automatica, 117 (108975), 2020.

| Links:

44.

P M J Van den Hof; K R Ramaswamy; S Shi; H J Dreef

Identifiability and data-informativity for single module identification in dynamic networks. Technical Report

2020, (Accepted as extended abstract in MTNS2020, but unpublished).

| Links:

45.

S Shi; X Cheng; P M J Van den Hof

Excitation allocation for generic identifiability of a single module in dynamic networks: A graphic approach Journal Article

In: IFAC-PapersOnLine, 53-2 , pp. 40-45, 2020, (Proc. 21st IFAC World Congress, Berlin, Germany).

| Links:

46.

S Fonken; M Ferizbegovic; H Hjalmarsson

Consistent identification of dynamic networks subject to white noise using weighted null-space fitting Journal Article

In: IFAC-PapersOnLine, 53-2 , pp. 46-51, 2020, (Proc. 21st IFAC World Congress, Berlin, Germany).

| Links:

47.

P M J Van den Hof; K R Ramaswamy

Single module identification in dynamic networks - the current status Inproceedings

In: Prepr. 21st IFAC World Congress, pp. 52-55, Berlin, Germany, 2020, (Extended abstract).

| Links:

48.

P M J Van den Hof; K R Ramaswamy

Path-based data-informativity conditions for single module identification in dynamic networks Technical Report

Eindhoven University of Technology 2020, (Extended report version of a paper presented at the 59th IEEE Conf. Decision and Control, Jeju Island, Republic of Korea, 15-18 December 2020. ).

| Links:

49.

P M J Van den Hof; K R Ramaswamy

Path-based data-informativity conditions for single module identification in dynamic networks Inproceedings

In: Proc. 59th IEEE Conf. on Decision and Control (CDC), pp. 4354-4359, IEEE Jeju Island, Republic of Korea, 2020.

| Links:

50.

T R V Steentjes; M Lazar; P M J Van den Hof

Data-driven distributed control via virtual reference feedback tuning Inproceedings

In: Proc. 59th IEEE Conf. on Decision and Control (CDC), pp. 1804-1809, IEEE Jeju Island, Republic of Korea, 2020.

| Links:

51.

V C Rajagopal; K R Ramaswamy; P M J Van den Hof

A regularized kernel-based method for learning a module in a dynamic network with correlated noise Inproceedings

In: Proc. 59th IEEE Conf. on Decision and Control (CDC), pp. 4348-4353, IEEE Jeju Island, Republic of Korea, 2020.

| Links:

52.

T R V Steentjes; M Lazar; P M J Van den Hof

Scalable distributed and decentralized H_2 controller synthesis for interconnected linear discrete-time systems Technical Report

2020, (ArXiv:2001.04875 [cs.sY]. Extended version of paper accepted for MTNS 2020.).

| Links:

53.

V C Rajagopal

An iterative algorithm for learning dynamic networks with correlated noise Masters Thesis

Eindhoven University of Technology, 2019, (Internship Report).

| Links:

54.

R van Esch

Topology detection in brain networks Masters Thesis

Eindhoven University of Technology, 2019.

| Links:

55.

X Chen

Centralized and distributed identified model based predictive control for museum Hermitage Amsterdam Masters Thesis

Eindhoven University of Technology, 2019.

| Links:

56.

H H M Weerts; J Linder; M Enqvist; P M J Van den Hof

Abstractions of linear dynamic networks for input selection in local module identification Technical Report

Eindhoven University of Technology 2019, (arXiv:1901.00348 [cs.SY]).

| Links:

57.

S Shi; G Bottegal; P M J Van den Hof

Bayesian topology identification of linear dynamic networks Inproceedings

In: Proc. 2019 European Control Conference, pp. 2814-2819, Napels, Italy, 2019.

| Links:

58.

K R Ramaswamy; P M J Van den Hof

A local direct method for module identification in dynamic networks with correlated noise Technical Report

Eindhoven University of Technology 2019, (ArXiv:1908.00976 [cs.sY]).

| Links:

59.

Cheng X.; S Shi; P M J Van den Hof

Allocation of excitation signals for generic identifiability of linear dynamic networks Technical Report

Eindhoven University of Technology 2019, (ArXiv:1910.04525 [math.OC]).

| Links:

60.

K R Ramaswamy; P M J Van den Hof; Dankers A G.

Generalized sensing and actuation schemes for local module identification in dynamic networks Inproceedings

In: Proc. 58th IEEE Conf. on Decision and Control (CDC), pp. 5519-5524, IEEE Nice, France, 2019.

| Links:

103 entries « ‹ 3 of 6 › »

 

103 entries « ‹ 3 of 3 › »

Inproceedings

2013

A G Dankers; P M J Van den Hof; X Bombois; P S C Heuberger

Predictor input selection for two-stage identification in dynamic networks Inproceedings

Proc. 2013 European Control Conference (ECC), pp. 1422-1427, 2013.

Links | BibTeX

A G Dankers; P M J Van den Hof; P S C Heuberger

Predictor input selection for direct identification in dynamic networks Inproceedings

Proc. 52nd IEEE Conf. on Decision and Control (CDC), pp. 4541–4546, IEEE 2013.

Links | BibTeX

2012

A G Dankers; P M J Van den Hof; P S C Heuberger; X Bombois

Dynamic network structure identification with prediction error methods - basic examples Inproceedings

J Schoukens; R Bitmead (Ed.): Proc. 16th IFAC Symposium on System Identification, Brussels, Belgium, pp. 876-881, 2012.

Links | BibTeX

103 entries « ‹ 3 of 3 › »